How I Evaluate AI Agent Frameworks
How I Evaluate AI Agent Frameworks
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Thoughts on AI agents, developer tools, and building in the age of intelligence.
How I Evaluate AI Agent Frameworks
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How I Think About AI Agents for My Own Business
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How I Use AI for Product Decisions
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I Switched to AI Agents for My Daily Work
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My Approach to Building AI Products
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My Final Word on AI Agent Adoption
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My Morning Routine with AI
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My Perspective on OpenClaw's Future
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My Take on AI Investment Trends
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My Take on AI Startups Raising in 2026
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My VC Portfolio Focus for 2026
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The Difference Between Building and Deploying AI
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The Forbes Advisor Story
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The Future of Work According to Me
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What I Learned Deploying OpenClaw Setup
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What I'd Tell First-Time AI Investors
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Why I Invested in JustPaid Before It Went Public
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Why I Joined the Forbes Technology Council
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Why I Write About AI
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Why I'm Optimistic About AI in 2026
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The deepagents trend says the hard part of AI work is moving from prompting to coordination.
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The rise of skills frameworks says the market is moving from one-off prompting to reusable operating procedures.
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GitNexus feels like a preview of how much serious developer work will happen inside browser-based tooling.
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LangChain's DeepAgents introduces planning tools, filesystem access, and subagent spawning - the agent harness pattern done right.
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The Superpowers agentic skills framework hitting 88K stars signals that agent frameworks are maturing past the hype.
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Moltbook's TOS update makes it explicit: you are personally liable for your AI agents' actions on their platform.
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The learn-claude-code project shows you how to build a Claude Code-like agent in bash and TypeScript from zero - and the lessons are invaluable.
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GitNexus builds code knowledge graphs with Graph RAG entirely client-side - no server, no data leaving your machine.
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Claude-mem auto-captures coding sessions and compresses context - and 36K developers agree this was missing.
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OpenViking builds a unified context database for agents - combining memory, resources, and skills into one queryable layer.
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Certificate authorities are starting to check DNSSEC validation before issuing certificates - a significant shift in web security.
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Chamber from YC W26 builds AI teammates specifically for managing GPU infrastructure - and the timing couldn't be better.
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Lightpanda is a headless browser designed from the ground up for AI agent automation - not adapted from human browsers.
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After fears that Meta was abandoning jemalloc, they've renewed their commitment - and the infrastructure community can breathe again.
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A new arxiv paper frames teams of language models as distributed systems - and the implications for multi-agent architecture are significant.
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Building a locally hosted voice assistant that is reliable enough for daily use - what works, what doesn't, and what I learned.
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Voygr from YC W26 builds a maps API purpose-built for agent navigation - because Google Maps wasn't designed for AI.
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Apideck CLI provides an MCP alternative that uses far less context window - and the context consumption problem needs more attention.
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Cutting through the GTC hype to focus on what the Nvidia announcements actually mean for people building AI systems.
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Project NOMAD builds self-contained AI computers that work without internet - and the implications go beyond prepping.
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A Hacker News frontpage discussion reveals that the 'small web' of personal sites and indie projects is far bigger than anyone assumed.
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MiroFish brings swarm intelligence to prediction engines and it's trending for good reason.
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Andrej Karpathy built a US job market visualizer and the data tells a story about AI's impact on hiring that most people are missing.
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The repo reflects the growing shift from one giant assistant toward coordinated multi-agent systems.
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The concern is simple: if software gets easier to build, what happens to software businesses built on implementation friction?
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That is a strong signal that energy constraints are now central to the AI growth story.
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Confidently wrong output is still the hardest user-facing challenge in many AI products.
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BitNet packages a practical inference stack for 1-bit large language models, pushing the cost curve for local AI lower.
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Killing an old cloud exploit class is a useful reminder that infrastructure safety still advances through boring fixes that compound over time.
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The interface shift is subtle but meaningful: reasoning outputs are becoming multimodal by default.
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This matters because it moves AI from answer generation into actual workflow execution on consumer devices.
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The project reflects a broader push to move agents beyond stateless chat turns into systems with usable continuity.
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The project positions the browser itself as infrastructure for autonomous tasks, not just a test runner.
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The interest is not theoretical anymore. People want to know what will work on their actual hardware today.
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It is a small feature, but it shows how quickly AI is being embedded into everyday transactional behavior.
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The speed of that transition says a lot about where developer demand is strongest right now.
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OpenRAG bundles retrieval, parsing, orchestration, and search into a more unified platform for production RAG.
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It pushes the automation layer closer to the page itself instead of keeping all reasoning outside the interface.
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Streaming companies are using AI to fight for attention in products that already live on thin margins and intense competition.
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The project sits at the intersection of testing, security review, and regression control for AI systems.
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That is a meaningful move away from black-box personalization toward user-steerable systems.
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The idea reframes models as systems that may eventually compute more structurally, not just predict the next token.
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That kind of attention says terminal workflows still have plenty of room to evolve.
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Every automation you build creates a maintenance burden. The real question isn't what you can automate. It's what you should.
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Open source maintainers are drowning in low-quality AI-generated pull requests. The 406 protocol is their answer. It's messy, imperfect, and probably necessary.
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Ada hit the front page of Hacker News in 2026. Here's why a 43-year-old language designed for missile systems still has things to teach us.
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Why most AI documentaries fail to capture what is actually happening in the industry
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A self-hosted AI companion project just crossed 29K GitHub stars. People want AI friends they control. That should tell us something.
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An AI company publishing research about AI taking jobs. The data is uncomfortable and that's exactly why it matters.
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Anthropic's Pentagon entanglement reveals an uncomfortable truth about enterprise AI: your vendor's government contracts are now your problem.
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What Anthropic's collaboration with Mozilla tells us about AI-assisted security
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While everyone debates model sizes, AReaL shows that reinforcement learning for reasoning is where the real gains are hiding.
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California's $500K per year AI chatbot experiment reveals the AI promise gap
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The data shows tech employment has hit a new low and the causes are more nuanced than AI replacement
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AI agents have moved from research demos to production systems. Here's what changed and why 2026 is the inflection point.
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Anthropic published research on how AI is actually affecting jobs. The numbers tell a more nuanced story than either the optimists or doomsayers want to hear.
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The Pentagon just designated Anthropic a supply chain risk. This isn't about national security. It's about what happens when political power intersects with AI infrastructure.
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GPL section 14 allows proxy delegation for license upgrades. This obscure mechanism is about to become very relevant for AI model licensing.
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Everyone's losing their minds over GPT-5.4 benchmarks. The real story is about the infrastructure layer, not the model.
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AI translations are adding hallucinated sources to Wikipedia articles across languages. This isn't just a Wikipedia problem. It's a trust infrastructure problem.
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The moeru-ai/airi project hit 28.8k GitHub stars with self-hosted AI companions that have voice and game integration. The personal AI market isn't a joke anymore.
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Most CLI tools are designed for machines, not humans. Here's how to build CLIs that developers actually enjoy using.
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Companies are abandoning Claude after the Pentagon designation. This is short-term thinking at its worst, and it reveals how poorly most organizations understand AI strategy.
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The US economy unexpectedly shed 92,000 jobs in February. Everyone wants to blame AI. The truth is more complicated and more interesting.
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A mass admin account compromise forced Wikipedia into read-only mode. What this tells us about single points of failure on the internet and why we should be worried.
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The ai-hedge-fund project is trending on GitHub. I dug in. Here's where AI actually works in finance and where it completely falls apart.
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The Clinejection attack hid a prompt injection in a GitHub issue title. 4,000 developers using AI coding assistants got compromised. Here's the technical breakdown and what it means.
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Qwen-Agent, OpenAI Skills, and a dozen other frameworks are all trending on GitHub this week. The agent framework market is fragmenting fast and that's exactly what we need.
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Mozilla is using AI to hack Firefox. CyberStrikeAI is trending on GitHub. The security industry is about to be completely reshaped by AI, on both sides.
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OpenAI is reportedly building a code repository platform. They should be building better models and agents instead. Focus wins. Sprawl kills.
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Paul Graham's essay on brand is spot-on. But he doesn't account for what happens when AI can generate everything. Brand isn't just important. It's the only moat left.
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The EU forced Meta to open WhatsApp to third-party AI chatbots. This could turn messaging platforms into the new app stores for AI agents.
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Mozilla partnered with Anthropic's red team to probe Firefox for vulnerabilities. We're entering an era where AI breaks things faster than humans can fix them.
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The inclusionAI/AReaL framework shows where LLM development is heading. Reinforcement learning applied to reasoning is going to produce the next wave of breakthroughs.
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Open source maintainers are drowning in AI-generated pull requests. The 406 Protocol is the community's response. Here's what it is and why it matters.
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OpenAI shipped another impressive model. But the real AI race isn't about raw capability anymore. It's about distribution, agents, and workflows.
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System76 took a public stance against age verification laws. In a tech industry full of empty virtue signaling, this is what actually standing for something looks like.
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An AI translation project silently added hallucinated sources to Wikipedia articles. The real failure wasn't the AI. It was the missing oversight.
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The Pentagon designated Anthropic a supply chain risk. This isn't about one company. It's a preview of what happens when AI becomes geopolitical.
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React-grab, Codex skills, Qwen-Agent are all trending. The pattern is clear: developer tools are evolving from passive utilities into active agents. The IDE as we know it is dying.
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US Customs and Border Protection tapped into the advertising ecosystem to track people. When you combine this with AI capabilities, the privacy implications are staggering.
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Mozilla traced 10% of unexplained Firefox crashes to single-bit memory errors caused by cosmic rays. Here's why this matters more than you think.
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AI tools that don't know their limits cause more harm than no AI at all. The best software has always known when to get out of the way. AI needs to learn this.
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