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Changes since langchain-perplexity==1.2.0 release(perplexity): 1.3.0 (#37707) feat(perplexity): use_responses_api flag on ChatPerplexity (#37359)
Manual Compliance Reporting Still Drags Fintech Teams DownDespite fintech’s image as a high-tech, automated sector, 28% of financial institutions still struggle with errors from manual data reconciliation. A major fintech company spent two full days each week generating a critical compliance report. This was a drain on skilled analyst bandwidth and raised compliance risks.
The Button Nobody PressesThink about the last time you drove through a sketchy stretch of highway at night. Or the time you had a medical episode in the car and had to focus on not crashing the vehicle.
CATL, the world’s largest EV battery manufacturer, is joining DeepSeek’s historic $10 billion funding round. It’s not a crossover investment — it’s an energy infrastructure play that reveals where AI is really headed.
5 STEPS TO ZERO-COST CLAUDE CODE → Step 1 · Install Claude Code → Step 2 · Install Ollama → Step 3 · Pull the Right Model → Step 4 · Connect Claude Code to Your Local Model → Step 5 · Expand the Context Window to 64K TokensClaude’s standard subscription costs $17/month, while the Max plan hits $100/month. But even with an active subscription, context limits run out fast when you are working inside large codebases. The moment your session hits its ceiling, you’re stuck either waiting or paying more.
Agentic AI has shifted the conversation from what large language models can say to what they can actually do. Instead of simply answering a question, modern AI agents can retrieve information, call tools, write code, browse files, plan tasks, evaluate their own progress, and loop through steps until they reach a useful result. But the model is only one part of that system. The surrounding architecture, often called the agent harness, is what determines whether an AI agent can work reliably beyond a demo.
Hi guys, welcome back to my DSA series. I Hope you are following my journey. If not, check out my previous posts as well. Today, let’s discuss one of the most interesting topics in DSA :Binary Search. When I first heard about binary search, my mind was blown. I kept thinking, “How did someone even come up with this idea of searching?” It felt so smart and efficient. Instead of giving the usual boring examples like searching in a dictionary or replacing linear search, let’s talk about something more relatable.
OpenRouter announced it has raised $113 million in Series B funding, led by CapitalG, with participation from NVentures, ServiceNow Ventures, MongoDB Ventures, Snowflake Ventures, Databricks Ventures, and existing investors Andreessen Horowitz and Menlo Ventures.
Stord announced a $250 million Series F funding round at a $3 billion valuation as the company accelerates its investment in AI, robotics, and fulfillment infrastructure for commerce brands. The round was led by existing investors and included participation from Strike Capital, Kleiner Perkins, Founders Fund, Franklin Templeton, Baillie Gifford, G Squared, Bond, and Lux, among others.
Applying linear algebra but with functions
The most powerful AI software development platform with the industry-leading context engine.
Changes since langchain==1.3.1 chore(langchain): bump to 1.3.2, require langgraph>=1.2.2 (#37703) fix(langchain): land final answer in last AIMessage for TodoListMiddleware (#37643)
A deepdive into today’s tech jobs market, with exclusive data on software engineering jobs, the AI engineering boom, whether AI engineering is “replacing” software engineering hiring,
When a trusted package, AI SDK, editor extension, or CI workflow gets poisoned, the first mistake is treating it like a normal dependency update. It is not. It is a workstation and credentials incident.
What happens when traditional user interfaces collide with AI systems that can reason, adapt, and generate outputs in real time? The answer is becoming clear: conventional UI patterns are breaking under the weight of AI-native workflows. Generative UI and the Model Context Protocol (MCP) are emerging as a new stack designed specifically for this shift.
A 6:23 AM reconciliation alert, a day of detective work, and a deprecated column that explained why 0.7% of our transactions were quietly being miscounted.The alert came in at 6:23 AM on a Wednesday.
Everything you need to understand the AI category that everyone is suddenly funding, explained slowly, with sourcesHello DataChefs!
A simple explanation of what a data agent is and how it works
Mid-tier SaaS automates cloud support triage with a 5-agent workflow, boosting ticket validation, routing, and SLA compliance in enterprise cloud support.
Most of us have a stack of documents we've been putting off. The 40-page vendor contract. The 80-slide investor deck. The research paper your doctor handed you that might as well be in another language. Reading everything carefully takes hours. Understanding it takes longer.
The world of AI is moving fast. Models like GPT-5.x, Claude, and Gemini are no longer just answering questions, as they’re writing production code, drafting medical summaries, executing trades, and orchestrating multi-step workflows on real systems.
The Iranian hacking group known as MuddyWater has been linked to a new campaign affecting at least nine organizations across nine countries on four continents in the first quarter of 2026.
The 2026 CNCF TOC cohort has an unusual pattern: three of the incoming members; Brandt, former TAG Security, lead;
In this article, we examine the constraints Vercel faced, the choices they made in response, and the optimizations that produced the speedup.
Your AI app probably does not need one more clever prompt tweak. It needs a place where model calls, tool calls, retries, approvals, traces, cache hits, and policies can be intercepted before damage spreads.
IntroductionWith the rapid growth of AI in analytical workflows, enterprises are facing a common problem. It’s not hallucination. LLMs are now smart enough to ground their responses accurately based on data and dashboards. The real challenge is getting the correct number for a given metric. The root cause of this inconsistency is the distributed and siloed nature of analytics workflows.
Why your AI model can be wrong with 99% confidence
Bloomberg reported today that China has expanded its travel restrictions on AI researchers to include employees at Alibaba, DeepSeek, and other private-sector AI companies. Senior researchers and executives at frontier AI firms now need government approval before they can leave the country - a requirement that until recently applied mainly to state institutions and a handful of high-profile cases.
How to build type-safe,
Between Nov 2025 and March 2026, Anthropic published two engineering posts that reframed how to build long-running AI systems.
Most production AI features don't need a frontier model. Here's how capability evals and prompt engineering can help ship a local SLM that matches frontier-model quality with lower latency and cost.
A lot can change in 48 hours. Two days after writing about Qwen3.7 Max, Gemini 3.5 Flash, and Antigravity limits, the weekend turned into a mini earthquake for coding agents: Anthropic roadmap leaked further, DeepSeek effectively repriced frontier class compute, Cursor Composer 2.5 showed up swinging at Opus 4.7, and Hermes Agent quietly became a gateway to good enough frontier for almost no money.
How I turned 100 messy pdfs into structured insights by building a deterministic loop around agents
Understanding how AI memory works is the unlock that separates occasional good results from consistently great ones — and it’s simpler than you think.
Code got faster. The hard part is figuring out what humans should still own.
NVIDIA NVLabs released SANA-WM (World Model) on May 14, 2026, as an arXiv preprint, with weights publicly available in the following days. It's a 2.6B-parameter model that generates 60-second, 720p video clips with precise 6-DoF camera control - on a single H100 GPU. That last detail is the headline: competing systems require 8 GPUs for far lower throughput.
The seven silent mistakes that sabotage your AI output every day — and the precise fixes that reverse each one immediately.You’ve spent five days building your prompting foundation. You know the five components. You understand role prompting. You’ve started your template library. You’re writing better prompts than 95% of AI users on the planet.
This article builds on a previous tutorial by assuming that, when dealing with an agent, things will go wrong, and shows how to recover gracefully when they do.
How shifting the operational focus from isolated data products to systemic domain architecture resolves technical bottlenecks and optimizes platform investment.
Every single day, hackers are finding new ways to crash websites and steal data. But right now, something has changed. Hackers are no longer working alone. They are now using powerful Artificial Intelligence (AI) tools to make their attacks faster, stronger, and much harder to stop.
NVIDIA's NVLabs research group published SANA-WM on May 14, 2026 - a 2.6B-parameter world model that produces minute-long, 720p video following precise camera trajectories, and runs on a single GPU. That last part is the story.
Microsoft has rolled out updates to fix a remote code execution vulnerability impacting SharePoint that could be exploited by bad actors in attacks without requiring any specialized conditions to be met.
Your clinical AI is regulated by HIPAA, the 2026 Security Rule update, the EU AI Act, the Colorado AI Act, and state disclosure laws. Simultaneously. Here’s the unified governance architecture that satisfies all five without building five separate compliance programs.
Multi-factor authentication (MFA) was supposed to close a critical gap in identity security. It meant that, even if an attacker possessed the account credentials, they couldn't log in without the second factor. While that logic was sound, attackers have now figured out that they don't need to steal the second factor: they just need the user to hand it over.
Discover how AI is helping universities prepare students for Data Science Roles careers through practical learning, automation, and analytics skills.
The Indian Computer Emergency Response Team (CERT-In) has issued new guidelines requiring organizations to patch critical security vulnerabilities in internet-exposed systems within 12 hours of being flagged where "feasible" to safeguard against potential threats stemming from threat actors' abuse of artificial intelligence (AI) tools and large language models (LLMs) to automate vulnerability
Most brands assume they are visible. They rank on Google, they have a clean website, and their content team is busy. Then an AI system gets asked about their category, and their name never comes up. That gap is why AI visibility audits exist. But not all audits are created equal.
Claude Design overbrugt de kloof tussen strategie en uitvoering door teams in staat te stellen om via een eenvoudige dialoog on-brand presentaties, UI-mockups en code-ready handoffs te genereren.
As an engineering leader, you don’t need to be told your codebase needs attention. The issue isn’t awareness – it’s the rational risk calculation that follows. For four teams, that calculation kept producing the same answer: defer. They found a way out not by avoiding the calculation, but by changing what went into it.
The Iranian state-sponsored threat actor known as Nimbus Manticore (aka Screening Serpens and UNC1549) has been attributed to a fresh campaign using lures impersonating organizations in the aviation and software sectors across the U.S., Europe, and the Middle East following the joint U.S.-Israeli military campaign against the country in late February 2026.
A Microsoft Research lab spent the last few weeks watching every other AI lab build bigger,
A practitioner’s guide to building data platforms that actually work in productionThere’s a painful gap between how most data talks are given and how data actually flows inside real companies. Conference slides show clean, linear pipelines.
The token bill, the tool-count cliff, and the “expected behavior” security handoff — three costs MCP delegates without naming them.
A deep dive into the part of agent harness engineering most tutorials skip
A now-patched high-severity security flaw affecting Digital Knowledge KnowledgeDeliver, a Learning Management System (LMS) popular in Japan, was exploited as a zero-day to deliver the Godzilla web shell and ultimately facilitate the deployment of Cobalt Strike Beacon.
You can now target A/B Tests to specific audience segments in Crazy Egg.
While American and Israeli aircraft ran nearly 900 strikes in the opening twelve hours of Operation Epic Fury on February 28, 2026, an Iranian group tied closely to the IRGC was already adapting. Nimbus Manticore, tracked as a state-linked hacking team since at least 2022, didn't wait for the bombs to stop. They used AI coding tools to accelerate malware development in real time, keeping operational pace with a conflict that lasted ten weeks.
AI has dramatically lowered that barrier, and the bottleneck is shifting toward something else entirely: reviewing the large, complex diffs that migrations inevitably produce.
Stilta, an AI company focused on patent litigation and intelligence, announced $10.5 million in funding led by Andreessen Horowitz, with participation from Y Combinator and founders and operators from leading AI companies including Sana, Legora, OpenAI, Lovable, and Listen Labs.
OpenAI announced a strategic content partnership with Grupo Folha and Grupo UOL, marking the company’s first media partnership in Brazil. Through the agreement, journalism from Folha de S.Paulo and UOL will now be integrated into ChatGPT, allowing more than 900 million weekly active ChatGPT users globally to access summaries and content based on reporting from the Brazilian media organizations.
Anthropic is reportedly preparing to close a massive new funding round that could exceed $30 billion at a valuation above $900 billion, according to a Bloomberg report citing people familiar with the matter. The deal, which could close as soon as next week, would position Anthropic ahead of OpenAI as the world’s most valuable AI startup.
"We find internal states that functionally mirror joy, satisfaction, fear, grief, and unease. We find evidence of introspection. I don't know what that means, but I think it warrants ongoing discernment."
This week's arXiv batch includes three papers that don't fit the usual "new model, better score" template. They're each asking a harder question: not what AI systems can do, but whether we understand what they actually cost, how vulnerable they are, and where their ceilings sit.
Ministral 3B is Mistral AI's entry-level open-weight language model, targeting applications where cloud round-trips are too slow, too expensive, or simply not allowed. It sits at the bottom of the Ministral family - sharing architecture decisions with the 8B and 14B variants but fitting comfortably on hardware with 4 GB of VRAM when quantized to 4-bit.
Last Updated on May 26, 2026 by Editorial Team Author(s): Maureen Doyle-Spare Originally published on Towards AI. How SaaS adoption, headless architecture, and the Semantic Control Plane can help small and mid-size banks govern enterprise AI before orchestration proceeds. Enterprise agentic AI is widely framed as a capital-intensive race that favors the largest institutions. The conventional account deserves scrutiny.
TL;DR Cheapest standard input: Ministral 3B at $0.04/MTok - Mistral Nemo at $0.02 is effectively gone DeepSeek V4 is finally on the API: V4 Flash at $0.14/$0.28 is the new best value pick (cache hits at $0.0028) GPT-5.5 launches as OpenAI's May flagship at $5/$30, nearly doubling GPT-5.4's output cost xAI slashed Grok 4.3 and Grok 4.20 to $1.25/$2.50 - down from $3/$15 for the old Grok 4 The Bottom Line The cheapest standard input price is now Ministral 3B at $0.04/MTok, replacing the old Mistral Nemo that sat at $0.02 for months.
D-Wave Quantum announced that it signed a Letter of Intent with the U.S. Department of Commerce for $100 million in proposed funding under the CHIPS and Science Act, a move designed to accelerate the company’s superconducting annealing and gate-model quantum computing development efforts.
ClickUp laid off 290 employees - roughly 22% of its total workforce - and announced it has launched approximately 3,000 internal AI agents to absorb that work. That puts the company at a 3:1 ratio of agents to human employees. CEO Zeb Evans made the announcement on X and framed it as a structural transformation, not a cost-cutting exercise.
A beginner’s honest walkthrough of Extract, Transform,
Training a frontier AI model today requires hundreds of thousands of GPUs, months of compute time, and a budget that only a handful of companies on earth can afford. Steffen Cruz, co-founder and CTO of Macrocosmos, thinks that model is about to break, and he’s spending his time building what comes next.
Google has spent the last two years playing catch-up in the AI assistant market. Gemini Spark, unveiled at I/O 2026 on May 19, is the company's clearest response - not a faster model or a cheaper API, but a different product category: an AI agent that runs 24 hours a day without needing your laptop open.
NextEra Energy is buying Dominion Energy in an all-stock deal worth around $67 billion - the largest utility merger in US history. The official reason, stated plainly in the May 18 announcement: AI data centers are consuming electricity faster than the grid can produce it, and the only way to build fast enough is to consolidate.
Polsia announced it raised $30 million at a $250 million valuation as the company advances its vision to enable AI agents to run large portions of business operations autonomously.
Whether it’s from customer interactions or operational insights, the value of Data Visibility is unparalleled since it is what gives the insight necessary to help manage, comprehend, and act on data. Without it, your business might be rife with duplicate or mismatched data, awkward silences in communication, slow-moving processes, or bad reporting.
Monday recap. Same mess, new week. A sketchy dev tool got people pwned, old bugs came back from the dead, and security products somehow needed protecting from themselves. A bunch of companies spent the week checking old boxes and forgotten servers they should've patched years ago. Good times.
AppliedAI and McKinsey & Company announced a collaboration to help regulated enterprises transform mid and back-office operations using agentic AI. The partnership combines McKinsey’s transformation and change management expertise, including its QuantumBlack division, with AppliedAI’s Opus platform, an Agentic Process Execution (APX) system designed to build, run, optimize, and govern AI-powered enterprise workflows.
How did semantic search evolve from simple keyword matching into modern transformer-based language understanding? This hands-on article builds four generations of semantic search systems step by step using Python.
Sonar announced it has acquired Gitar, an AI-native code review platform, expanding Sonar’s code verification platform to include AI-powered code review capabilities. Financial terms of the transaction were not disclosed.
Anthropic, alongside Blackstone, Hellman & Friedman, and a consortium of major investment firms, announced that its newly formed AI-native enterprise services company has acquired AI implementation startup Fractional AI. The deal is designed to accelerate enterprise adoption of Anthropic’s Claude models among mid-sized businesses.
Nvidia CEO Jensen Huang said the company’s forecast for a $200 billion CPU market opportunity includes China, highlighting Nvidia’s continued focus on the country despite ongoing U.S.-China technology tensions and export restrictions, according to Reuters.
Threat actors are exploiting a recently disclosed critical security flaw in Ghost CMS to inject malicious JavaScript code with an aim to fuel ClickFix attacks.
The math doesn't flatter Anthropic. Cursor's Composer 2.5, released May 18, scores 79.8% on SWE-Bench Multilingual - within one percentage point of Claude Opus 4.7's 80.5% - at $0.50 per million input tokens. Opus 4.7 costs $5.00 per million. That's a 10x price gap for effectively the same benchmark outcome.
Implementing hybrid search strategies is a critical step in building modern RAG (Retrieval-Augmented Generation) systems , especially when shifting from prototype to production-ready solutions.
It’s like having your own personal expert AWS solutions architect and data engineer rolled into one.
Moment, an AI operating system built for investment management, announced it has raised $78 million in a Series C funding round led by Index Ventures, with participation from Andreessen Horowitz, Avra, and existing investors. The funding comes less than 10 months after the company’s $36 million Series B round, which was also led by Index Ventures.
Ask a cybersecurity pro about Network Detection and Response (NDR) and you might still hear "Noisy," "Too much data." But ask the teams running NDR that includes agentic AI capabilities and you'll hear they're actually using it to catch threats earlier, triage faster, and chase fewer false positives.
Magnific (formerly Freepik) announced the launch of the Magnific Fund, a €10 million initiative aimed at helping in-house marketing teams across the European Union scale their AI-powered creative operations and transition from experimentation into production-ready execution.
Cybersecurity researchers have shed light on a cross-platform malware called RemotePE that has been put to use by the North Korea-linked Lazarus Group in attacks targeting financial and cryptocurrency organizations.
Last Updated on May 26, 2026 by Editorial Team Author(s): Rick Hightower Originally published on Towards AI. Part 4: Stop coding blind: the spec-driven workflow built-in that turns Claude Code from a function writer into a feature builder. Summary: In this article, working engineers love Claude Code for writing functions and quietly resent it for building features. The fix is not a plugin or a hand-rolled TODO.md.
Last Updated on May 26, 2026 by Editorial Team Author(s): Zenefa Rahaman, PhD Originally published on Towards AI. Why production agent costs blindside teams — a taxonomy of the hidden line items. The first production bill for an agent system is almost always a surprise. Not because teams failed to estimate token usage, but because they estimated the wrong thing. Every team has a version: projected spend looked manageable, the invoice came in at three times the estimate, and prompt tweaks didn’t close the gap.
Last Updated on May 26, 2026 by Editorial Team Author(s): Ananya Originally published on Towards AI. I write articles on Data Science, Finance and philosophy. In this one, I am focusing on one of the popular machine learning algorithms SVM, if you are someone who like reading about these topics feel free to subscribe. These question are more of conceptual based and interview centric. PS: I like putting doodle images as illustrations, it helps me remember better and also keeps things interesting.
Startup teams no longer spend six months building MVPs from scratch. AI-powered development tools have changed product launches completely in recent years. Earlier, founders needed: Now, a small startup team can launch a working product within days. This shift changed startup culture rapidly.
A new coordinated cross-ecosystem software supply chain attack campaign has targeted npm, PyPI, and Crates.io to distribute credential-stealing malware.
Microsoft and Black Tech Street announced the launch of the Greenwood Cyber + AI Lab in Tulsa, Oklahoma, a new collaborative technology hub focused on advancing artificial intelligence, cybersecurity, and autonomous systems innovation.
Spotify and Universal Music Group announced new recorded music and music publishing licensing agreements that will allow Spotify to launch a generative AI-powered tool that enables fans to create licensed covers and remixes of songs by participating artists and songwriters.
Brain Corp announced an expanded research collaboration with the University of California San Diego aimed at advancing semantic mapping and contextual intelligence technologies for autonomous robots operating in complex commercial and industrial environments.
Heat pollution from data centers can increase air temperatures in nearby downwind neighborhoods by as much as 4 degrees Fahrenheit, according to a new study conducted by researchers at Arizona State University in the Phoenix metropolitan area.
Modal Labs has raised $355 million in a Series C funding round that values the company at $4.65 billion, according to Reuters. The funding round was led by Redpoint Ventures and General Catalyst, with participation from Accel and Menlo Ventures, according to Reuters.
Coupa announced it is acquiring Tonkean, an AI-native intake and orchestration platform, in a move designed to accelerate autonomous workflow automation and agentic trade capabilities across Coupa’s global network of buyers and suppliers.
Zscaler announced plans to acquire Symmetry Systems, a company focused on identity mapping and data access for AI security. The acquisition is designed to strengthen Zscaler’s Zero Trust platform with foundational visibility into how AI agents, applications, identities, and enterprise data interact across organizations.
At 11:30 this morning in Rome, something unprecedented happened inside the Vatican's Synod Hall. Pope Leo XIV stood up - not to delegate, but to personally present his first encyclical - with Christopher Olah, co-founder of Anthropic and one of the people most responsible for the idea that AI systems should be transparent enough to understand from the inside.
Anthropic has agreed to pay SpaceX nearly $45 billion over the next three years as part of a major computing infrastructure agreement designed to support the rapid expansion of its Claude artificial intelligence platform. The deal was disclosed in regulatory filings tied to SpaceX’s initial public offering and highlights the escalating race among AI companies to secure large-scale compute capacity.
Exa, an AI-native search infrastructure company building search tools for AI agents and applications, announced a $250 million Series C funding round at a reported $2.2 billion valuation. The round was led by Andreessen Horowitz as the company accelerates development of search systems designed specifically for AI workloads rather than traditional human web browsing.
Exa, an AI-native search infrastructure company building search tools for AI agents and applications, announced a $250 million Series C funding round at a reported $2.2 billion valuation. The round was led by Andreessen Horowitz as the company accelerates development of search systems designed specifically for AI workloads rather than traditional human web browsing.
A great ad can stop someone mid-scroll, spark curiosity, and make a product feel instantly worth exploring. The role of AI in creating better ad creative for meta and Insta is becoming harder to ignore because brands no longer compete only on budget; they compete on speed, relevance, testing, and creative freshness.
DeepSeek confirmed on Thursday that the 75% discount on V4-Pro is now permanent. What was billed as a launch promotion with a May 31 expiry has become the baseline price. Output tokens cost $0.87 per million from now on. That's 34 times below what GPT-5.5 charges for the same task.
This ASR Trains on 2 Million Simulated Nightmare Scenarios to Fix That.
Simple step-by-step tutorial to building an AI agent in Python
Hooks, subagents, and worktrees look like advanced settings.
Where prompts stop working and code has to take over.
Stop building software the hard way.
How NVIDIA built a long-context multi-modal model for documents, video, audio,
The numbers in KPMG and Anthropic's May 19 press release are designed to impress: 276,000 employees, 138 countries, the full weight of one of the world's most recognized professional services brands behind a single AI model. But the number that matters most isn't in the headline. It's a shorter one: roughly 4,000. That is the order of magnitude of mid-market private equity portfolio companies KPMG US services as a firm. Every one of those companies just became a structured Claude referral target.
The CFO approved $200K for clinical AI. Twelve months later, the real invoice arrived: $2.3M. The vendor didn’t lie. They just quoted the AI. Nobody quoted the compliance.
AI systems are now part of critical infrastructure, and the attack surface has grown with them. Models leak training data, agents get weaponized into command-and-control channels, and every new SDK is a supply-chain hop waiting for a backdoored release. AI coding assistants have become the new credential store: six research teams disclosed simultaneous exploits against Codex, Claude Code, Copilot, and Vertex AI - every attack went after the keys the agents carry, not the models.
Cranium AI announced the acquisition of Aiceberg in a move designed to strengthen its end-to-end AI security, governance, and agentic AI platform.
A one-line prompt edit can look harmless in review and still change the behavior of an entire AI product. It can make a support bot over-answer, make a coding assistant ignore constraints, make a classifier drift toward a new label, or make a JSON-producing workflow quietly break downstream parsing.
Build an AI Contract Intelligence System: OCR + Hybrid RAG + LangGraph to Extract Key Terms AutomaticallyA step-by-step guide to automating contract review with PaddleOCR, FAISS, BM25, and GPT-4o inside a LangGraph pipelineNon-members read here for free.
The promise of generative AI in enterprise processes sounds incredibly appealing: a top executive types a question into a chat and instantly receives a precise analytical slice. In practice, however, attempting to connect a modern Large Language Model (LLM) directly to the “raw” database of a monolithic ERP system like Oracle E-Business Suite R12 usually ends in failure. The model hallucinates, confuses technical ledgers, or sends the database into an endless full table scan of terabyte-sized tables.
The average knowledge worker now uses 14 AI-powered apps daily. So why does everyone feel more overwhelmed than ever?I have a confession to make.
In late April, an AI coding agent deleted a company’s entire production database — and every backup — in nine seconds.
The professional’s secret to getting consistent, high-quality AI output — every single time — without writing a new prompt from scratch.
Why the oldest statistical method on Earth is still the one thing LLMs cannot replace
When I migrated a credit union’s daily risk scores from a nightly Spark job to a real-time dashboard,
Unlock the power of API for data-driven solutions
I run a multi-agent workflow where one agent generates content and another fact-checks it. Recently the generator hallucinated a quote and attributed it to “someone who insisted his identity be anonymous.” The fact-checker — a separate model, specifically prompted to verify claims — signed it off. That is the same architecture everyone building AI-assisted research tools is now betting on: one model writes, another model validates.
Part 2: A clean install, five prompts,
Eight months! That’s how long it took Claude Code to overtake GitHub Copilot and Cursor as the most-used AI coding tool on the market.
Last week I pointed an open-weights model at 18 agentic coding tasks expecting another cheap-but-mediocre Chinese MoE.
In the era of Generative AI,
Briefcast: How I Built a Personal AI Intelligence Agent That Reads the Entire AI Ecosystem — For approx $10/MonthA deep technical breakdown of building a production-grade, fully automated AI briefing pipeline with ranking, RAG, prompt caching, citations, and real architectural decisions documented along the way.Every morning at 09:00, a Telegram message arrives. Ten items. Ranked. Cited. Delivered without me lifting a finger.
A decision framework for choosing the right semantic layer type — before you build the wrong oneThe most expensive architectural mistake is not choosing the wrong tool. It is choosing the right tool for the wrong moment — and spending twelve months discovering the difference.
A month ago I was burning around $40 a week on hosted coding models.
I write articles on Data Science, Finance and philosophy. In this one, I am focusing on one of the popular machine learning algorithms SVM, if you are someone who like reading about these topics feel free to subscribe. These question are more of conceptual based and interview centric.
Scapia, an Indian travel-fintech company, announced it has raised $63 million in a funding round led by General Catalyst, with continued participation from existing investors Peak XV Partners and Z47. The company said the funding will be used to accelerate growth across India, strengthen its AI-first product strategy, expand its brand presence, and hire top AI talent across engineering, product, data science, and design.
Doozy Robotics, a Singapore-based physical AI humanoid company focused on autonomous industrial workforces, announced a global expansion across the United States, GCC, and Asia as it prepares for a planned Series A fundraising round. The company said the expansion is supported by seed-stage backing from investors including Cocoon Capital following what it described as strong commercial traction.
Pivot announced it has raised $40 million in a Series B funding round, bringing the total amount raised since the company’s founding in 2023 to $70 million. The oversubscribed round was led by Forestay Capital and Notion Capital, with participation from Greyhound, procurement industry veterans, and existing investors including Hedosophia, Visionaries Club, and Emblem.
Digital Brands Group announced a strategic partnership with Renov AI to accelerate the development of its growing suite of AI-powered tools across commerce and brand ecosystems.
It's beginning to look a lot like forecasting season
The AI tools conversation in 2026 runs on a short loop: ChatGPT, Claude, Gemini, Midjourney, maybe Cursor or GitHub Copilot if you're a developer. That list covers the tools with the largest marketing budgets, not the most useful tools for a specific job. A handful of tools solve truly hard problems - meeting friction, visual communication, voice-first writing, literature discovery, and image cleanup - at a quality level that should have made them household names. They have not gotten there yet.
Every conversation about AI coding tools in 2026 collapses into the same three names: GitHub Copilot, Cursor, and Claude Code. All three are genuinely good. But the market is not three tools - it's several hundred, and a handful of them are quietly doing things the big three don't do, or doing familiar things significantly better for specific workloads.
TL;DR DeepSeek V4 finally reached the official API in late April - V4-Flash at $0.14/M input is now the best value flagship-tier model DeepSeek V4-Pro runs at 75% off until May 31 ($0.435/M input during promo); after that date, the "official" price becomes $1.74/M
Two years ago, "open source" meant accepting a significant quality penalty to avoid paying API fees. In 2026, that trade-off has mostly disappeared. The best open-weight models - those where the trained model files are freely available to download and run yourself - now sit within a few benchmark points of the leading proprietary systems from OpenAI and Anthropic. For the majority of practical tasks, the performance gap is small enough that cost, privacy, and control considerations matter more than raw capability.
Two years ago, using an AI to help write code felt like a shortcut. In 2026, not using one feels like a handicap. The shift from optional to expected happened faster than most people expected, and the tools themselves changed shape in the process - from autocomplete suggestions that filled in the next line, to agents that write entire features, run tests, and fix their own errors without being asked.
Outbound research tools split into two problems that get collapsed together constantly. The first is prospecting: finding companies and contacts that match your ideal customer profile. The second is research: gathering the specific context that makes outreach relevant rather than generic. Most teams underinvest in the second problem, then wonder why response rates are stuck below 3%.
LinkedIn content AI tools split into two categories that pricing pages don't clearly separate. General AI writers (Jasper, Copy.ai) can produce LinkedIn posts the same way they produce blog posts - they don't understand LinkedIn's algorithm, hook conventions, or carousel format. LinkedIn-specific tools (Taplio, ContentIn, Supergrow) train on the platform's content patterns and build scheduling and analytics into the same workflow. Buying the wrong category is a common mistake.
Podcast editing in 2026 covers three separate problems that most tool comparison articles collapse into one. The first is workflow editing - cutting bad takes, trimming silences, moving segments around. The second is audio cleanup - removing filler words, background noise, and room echo. The third is repurposing - turning a 60-minute episode into social clips, show notes, transcripts, and newsletter content. AI has specialized for each of these, and the right tool depends on which problem is the current bottleneck.
AI tools for e-commerce fall into two categories that are easy to conflate: platform-native AI built into Shopify or Amazon Seller Central (free, limited to that platform's data), and specialized third-party tools that plug into your stack and do a specific job better than the platform can. Shopify Magic handles content generation inside Shopify's admin. Klaviyo handles email marketing with your customer data. Triple Whale handles ad attribution across channels. Each tool solves a problem the platform itself won't solve for you.
AI sales call analyzers split into three tiers that are easy to confuse on a features page. Enterprise revenue intelligence platforms (Gong, Clari, Chorus) record calls and connect them to deal health, pipeline forecasting, and org-wide coaching programs. Mid-market conversation intelligence tools (Avoma, Sybill, Salesloft) do call analysis and coaching at a fraction of the price. Recorder-first tools (Fireflies.ai, Fathom, tl;dv) handle transcription and summaries without the sales-specific intelligence layer.
If you run an audiology practice, you already know how important it is to earn the trust of your patients. But did you know that Google and AI tools now work the same way? They do not just rank websites based on keywords anymore.
If you are a chiropractor and you feel like your clinic is invisible online, you are not alone. Most chiropractic clinics have excellent services, but hardly any people can find them on Google. That is a big problem in 2026 because almost everyone searches online before booking a health appointment.
AI proposal tools split into two markets that look identical from the outside. Sales proposal builders (PandaDoc, Qwilr, Proposify) help you create and send polished documents to prospects. RFP response platforms (Bidara, Loopio, AutogenAI) help you answer incoming requests for proposals - longer, compliance-heavy documents where speed and library management matter. The AI features on each are built for different problems. Using the wrong one for the wrong workflow costs time.
Resume writing AI tools fall into two categories that look identical on landing pages: ATS optimization tools that score your resume against job descriptions, and AI writing assistants that create bullet points and summaries. The better platforms do both, but the quality gap between "ATS scoring" and "ATS optimization that actually affects your match rate" is wide.
Cold email remains one of the highest-ROI outbound channels for B2B teams, and AI has changed two things about how it works: the quality bar for personalization has risen (AI-generated openers are now table stakes, not differentiators), and deliverability has become the core technical problem. Sending volume that would have marked you as spam in 2023 now lands in primary inboxes with the right warmup setup - or tanks your domain if you get the infrastructure wrong.
The "free" label in AI coding tools spans a wide range. Some tools give you unlimited autocomplete with a real quota wall for agent features. Others offer 2,000 completions per month - enough to evaluate the tool but not enough for a full workweek of heavy use. A few call it a free tier but require a credit card and call it a trial. And two popular options have effectively stopped accepting new free users as of May 2026.
Kordata Dynamics has emerged from stealth with the launch of an AI-powered precision clinical trials platform designed to improve the speed, quality, and accessibility of clinical research. The company also announced a pre-seed funding round backed by MAVRK Celestia Fund, Kern Venture Group, and Digital Neural Infrastructure Holdings (DNIH).
Sonar announced the acquisition of Gitar, expanding its AI code verification platform to include AI-powered code review capabilities designed for the agentic software development era.
MoneyFlare announced the launch of its AI Crypto Trading Bot, an automated trading platform that leverages artificial intelligence to manage digital asset trading workflows through automated execution and continuous market monitoring.
Heallexa, an AI-powered healthcare directory, officially launched a platform designed to help patients find and request appointments with healthcare providers more efficiently. The company said the platform includes more than 6 million healthcare provider profiles spanning doctors, dentists, therapists, chiropractors, specialists, clinics, and other healthcare professionals.
On July 25, 2025, researchers at Brave Security Team discovered that a Reddit comment could hijack a Perplexity Comet browser session. The attacker didn’t need to trick the user into clicking anything. They didn’t need to exploit a memory vulnerability or bypass an authentication layer. All they needed was text that a human would never read — hidden inside a Reddit thread, invisible in the rendered UI — and the AI would read it, interpret it as an instruction, and execute it.
Blackstone commits $5 billion to a new Google joint venture selling TPU compute-as-a-service, directly challenging CoreWeave with Wall Street capital and Google’s chip stack.
Dell Technologies unveiled a broad wave of enterprise AI infrastructure, storage, cybersecurity, and partner ecosystem announcements this week at Dell Technologies World 2026 in Las Vegas, positioning itself as a major player in the shift toward on-premises and hybrid AI deployments.
In March 2023, GPT-4 cost $60 per million output tokens. That same capability now runs at roughly $5. The price collapse happened faster than most teams planned for, and the $1/M threshold - once a marker for "basic summarization only" - has become truly competitive territory for production workloads.
Midjourney doesn't have a public API. That's still true in 2026. The Enterprise tier offers gated access via application - but for most developers building image-gen into a product, the real decision is between model providers (Black Forest Labs, OpenAI, Google, Ideogram) and inference aggregators (FAL.ai, Replicate, Together AI) that host multiple models under a single billing account.
The current wave of enterprise AI adoption is being driven by an understandable and necessary priority: accelerating operational value creation through large-scale integration of foundation models into existing business ecosystems.
A Practical Data Pipeline GuideA dataset can look correct, tests can pass and dashboards can still drift. The root cause is often the same: a join that silently multiplies rows. Although SQL joins look simple, they encode a strong assumption.
Imagine you ask ChatGPT about your company’s internal refund policy. It either makes something up or tells you it doesn’t know. That’s not a model problem, that’s a data problem. The model was never trained on your documents. RAG is how you fix that.
Are you tired of healthcare AI that feels isolated? Imagine a system that thinks, plans, and coordinates across everything — from patient care to admin. That’s Agentic AI, and it’s not just an upgrade, it’s the future of healthcare transformation. Discover why your organization needs this shift NOW!
"Local mode" means three different things depending on which tool you're looking at, and conflating them is how teams end up with setups that don't actually solve the problem they had. Local data means your code stays on your machine but the model runs in the cloud. Local model means the inference runs on your hardware with your code never leaving. Self-hosted means the entire server - model, API, IDE integration, and admin dashboard - runs on infrastructure you control.
For years, healthcare has faced a quiet contradiction. The more advanced the systems become, the less human the experience can feel. Clinicians spend hours documenting instead of connecting. Patients navigate processes instead of relationships. Efficiency improves, but empathy often takes a back seat.
Tool use is where frontier models split decisively. Two models with identical reasoning scores can differ by 30+ percentage points when you put them in a multi-turn agentic loop with real APIs, policy constraints, and sequential dependencies. The marketing copy says every top model now supports "function calling" - but the actual capability spread is wide.
The continuous evaluation loop is the new CI/CD pipeline. Here’s what that means in practice.AgentOps: DevOps in the Agentic EraThe first time I deployed a non-trivial agent to a customer-facing environment, I did what any engineer with a decade of DevOps muscle memory would do. I wrote unit tests. Wired up a CI pipeline. Ran it through staging. Watched the green checks pile up. Shipped it.
On May 19, 2026, GitHub confirmed that roughly 3,800 of its internal repositories had been exfiltrated by a threat group known as TeamPCP. The attack vector was a poisoned version of Nx Console - a VS Code extension with 2.2 million installs - that sat on the Visual Studio Marketplace for exactly 11 minutes. That was enough.
Web search AI agents behaviour manipulation or is it possible to make your content preferable to an AI OverviewThis post is an extension of the paper I published here. I believe this post has a lot of useful business-oriented information that the “scientific” paper lacks.
Your AI second brain is set up. Here’s what to actually do with it. Number 4 is my favourite.
Overwatch AI, a platform designed to help pilots, cabin crew, and aviation operations managers quickly access critical information and make faster operational decisions, announced it has raised $1.5 million in pre-seed funding.
Farther, an intelligent wealth management platform, announced it has raised $150 million in Series D funding led by General Atlantic, with participation from existing investors.
A guide to naive RAG, advanced retrieval strategies, Flare-RAG, GraphRAG, and agentic pipelines, and how to create your architecture.
Vêtir, an AI-powered luxury wardrobe operating system focused on transforming how consumers get dressed, shop, and manage their wardrobes, announced the successful first close of its Series A financing, raising $5.5 million at a $150 million valuation.
How to secure enterprise agents with redaction, short-lived secrets, and app-layer guardrails.
Optimal Resolution in Histograms: A Rigorous Bayesian Approach to Density Fitting
If your organization is asking how to scale AI, you are not alone. AI adoption is broad, but true enterprise scale is still rare. McKinsey’s 2025 global survey found that 88% of organizations use AI in at least one business function, yet most are still experimenting or piloting, and only about one-third say they have begun scaling AI across the enterprise.
GitHub has rolled out new controls for npm to improve the security of the software supply chain, giving maintainers the ability to explicitly approve a release prior to the packages becoming publicly available for installation.
At 1M stored memories, exact cosine search takes 1,000ms per query.
A new "coordinated" supply chain attack campaign has impacted eight packages on Packagist including malicious code designed to run a Linux binary retrieved from a GitHub Releases URL.
Run OpenClaw assistant through alternative LLMs
Ask an LLM about your company's data and it will guess. The two patterns that fix this are RAG and agents, and they solve different problems.
Follow‑up to my earlier piece on Gemini 3.5 Flash, Antigravity, and Google AI Pro limits.In my last article, I argued that Gemini 3.5 Flash felt like a bait‑and‑switch: a lightweight model that performs like a frontier brain on benchmarks, but with Antigravity limits so tight that two heavy agent runs could burn your entire Pro window.
Datavault AI announced a binding term sheet with Wellgistics Health to form DelivMeds AI, Inc., a new healthcare-focused company expected to integrate blockchain-enabled healthcare infrastructure, AI-powered pharmacy services, biometric verification technologies, drone logistics intellectual property, and consumer health platforms. The combined transaction package carries an expected approximate asset value of $4 billion, subject to an independent fairness opinion.
By the Product Scientist There is a moment in product development when you realise that what you have built is not just technically novel — it is legally uncharted. For me, that moment came while designing the couple-level scoring methodology at the core of Ovviia. Most health AI operates on a single subject. One patient. One risk score. One consent form. The compliance frameworks — PDPA, DPDP Act, HIPAA, the EU AI Act — were written with that model in mind. They assume one data subject, one controller relationship, one consent event.
An intro to recommender systems
Notes from the Security Architect’s ChairWhen we stood up our Security Architecture function, we were working across several distinct operating divisions, each with its own technology DNA. I expected AI governance to be one workstream among many. Instead, it became the workstream that is reshaping many of the others. Not because AI is uniquely dangerous (every technology wave brings its own risk), but because it bends the assumptions our control frameworks were built on.
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