Skills can allow you to have deterministic execution patterns, so I have a lot of minimal harnesses for repeated tasks, that way I can control outcome no matter what model I use This is extremely helpful if you have multiple endpoints / models that you want to run in parallel
AGENTS
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Free chatbots vs costly high-capability AI agents
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Everyone on earth will get really good chatbots for free, so thats good for democratization of AI, but really good agents that can do complex work burn thousands of times more tokens, and will be reserved for places that can afford to pay, which is bad for democratization.
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Compute limits will favor agentic AI over chatbots
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We are quite short of compute, and that is going to result in compute becoming very expensive for complex agentic workflows even as single-turn chatbots get cheaper. So the richest companies & most pressing use cases will use AI agents & everyone else will be stuck with chatbots?
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Daytona’s Agent-Native Compute Explained: AI Agents Need Composable Computers
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🆕Daytona’s Agent-Native Compute: 60ms sandboxes, 50K startups in 75 sec, 850K daily runs, RL/evals, CLI > MCP, & the end of localhost https://t.co/3sauItT6oc@daytonaio CEO @ivanburazin explains why AI agents need composable computers, how Daytona pivoted from human dev… pic.twitter.com/WGjlPJwpEr
— Latent.Space (@latentspacepod) 21 mai 2026Daytona’s Agent-Native Compute: 60ms sandboxes, 50K startups in 75 sec, 850K daily runs, RL/evals, CLI > MCP, & the end of localhost https://
latent.space/p/daytona @daytonaio CEO @ivanburazin explains why AI agents need composable computers, how Daytona pivoted from human dev -
Vibecoded App to Production-Ready AI Agent Repo
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working on a "take this vibecoded slop app and make it a production-ready, e2e tested, maintainable, parallelizable agent repo" skill. this thing ran for ~16 hours yesterday and made 103 commits all told and i ended up with exactly the same app but instead of fragile mvp it
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Datasette Agent Alpha: Conversational AI for SQLite Databases
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I released the first alpha of Datasette Agent – a conversational AI assistant for Datasette that can answer questions about data in SQLite databases, and can be extended with plugins to add extra tools and features
— Simon Willison (@simonw) 21 mai 2026
Here's a demo pic.twitter.com/2gyduf5EphI released the first alpha of Datasette Agent – a conversational AI assistant for Datasette that can answer questions about data in SQLite databases, and can be extended with plugins to add extra tools and features Here's a demo
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The Unpredictable Nature of AI Agents in Production
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The hardest truth about building agents? You don’t know what they’ll do until they’re in production… pic.twitter.com/PnPrX7nuUz
— LangChain (@LangChain) 21 mai 2026The hardest truth about building agents? You don’t know what they’ll do until they’re in production…
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Databox Evaluates Multi-Turn Analyst Agent Genie Using LangSmith
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@DataboxHQ uses LangSmith to evaluate their multi-turn analyst agent Genie. An inside look: https://
databox.substack.com/p/how-we-evalu
ate-a-multi-turn-agent
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Active Graph video: flipped agent architecture, blackboard system, self-improvement
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longer form video on Active Graph [7 min 22 sec]
— Yohei (@yoheinakajima) 21 mai 2026
– flip the agent architecture
– 1970s blackboard system
– rollback, fork, diff agent runs
– experience + behaviors + beliefs = you
– behaviors can write behaviors (self-improvement)
github: https://t.co/8ENyNt4gYD pic.twitter.com/WeN2D60bdjlonger form video on Active Graph [7 min 22 sec] – flip the agent architecture
– 1970s blackboard system
– rollback, fork, diff agent runs
– experience + behaviors + beliefs = you
– behaviors can write behaviors (self-improvement) github: https://
github.com/yoheinakajima/
activegraph
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Building Applications with Streaming AI Agents
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Streaming agents should feel like building applications, not parsing logs.