The hand-wringing over token usage is real, but I don’t see any organization that has adopted AI retreating from use in coding or even considering it. We are a few months into agentic coding, and companies are trying to experiment with approaches to balance adoption & efficiency
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Reconstructing Software Engineering for AI-Driven Coding
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Reconstructing software engineering around AI is going to take work (even as the ability of AI to code increases at a rapid rate). Organizations are ideally spending tokens for two things:
1) building stuff
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Harness Profiles for Multi-Model Prompt Optimization
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Different models need different prompts, sometimes tools “Harness profiles” are how we do that in deepagents
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Model Release Cycles: Anthropic & OpenAI Speed Advantage
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The model release cycles from Anthropic & OpenAI are genuinely insane, previously we had 6-12 months between updates, now models are released every 1.5 months. This is an under-appreciated reason why Anthropic & OpenAI are in the lead. Google's releases are not as fast,
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AI Applications for Regulated Enterprises with Governance
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@Dominodatalab
’s Matt Bonyak and Danny Stout at #Rev26: regulated enterprises don't have a model problem. They have an application problem. AI apps built and deployed in hours, governance included. #Rev26 -
Five Million AI Agents Tracking Public Data on Billions
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This guy has five million AI agents tracking everything publicly available about three billion people!
— Robert Scoble (@Scobleizer) 29 mai 2026
He spent half a million bucks doing that.
Be scared? Or be educated? @michaelfanous1 runs https://t.co/cPDcSWapT6 and I have a lengthy conversation about what he's doing and… pic.twitter.com/Q418BEQQDRThis guy has five million AI agents tracking everything publicly available about three billion people! He spent half a million bucks doing that. Be scared? Or be educated? @michaelfanous1 runs https://
nyne.ai and I have a lengthy conversation about what he's doing and -
Use Claude to Interview Requirements for an AI Project
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5. Interview For anything ambiguous, don't write the full spec yourself. Make Claude extract it: "I want to build [rough idea]. Before we start, interview me. Ask me one question at a time about requirements, constraints, edge cases, and what done looks like. Keep asking until
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Prompt: Grill the AI to defend code changes
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2. The Grill After Claude says it's done, don't trust it. Make it defend the work: "Grill me on these changes. Diff your work against main, find every assumption you made, every edge case you didn't handle, and every place this could break in production. Don't open a PR until
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Plan-first prompt for feature development
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1. Plan-First Lock Before any feature, paste this: "Before writing any code, explore the relevant files and explain your plan for [feature]. List the files you'll change, the approach for each, and any edge cases you see. Do not write a single line until I approve the plan."
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Anthropic’s Claude Opus 4.8 and 7 Claude Code Prompts
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Claude Opus 4.8 just dropped. Anthropic says it's 4x less likely to let flawed code slip through than 4.7.
— God of Prompt (@godofprompt) 29 mai 2026
But the model is only half of it. The other half is how you prompt it.
Here are 7 Claude Code prompts the best builders already run on repeat. Steal all 7: 👇 pic.twitter.com/bBX5KXnmCMClaude Opus 4.8 just dropped. Anthropic says it's 4x less likely to let flawed code slip through than 4.7. But the model is only half of it. The other half is how you prompt it. Here are 7 Claude Code prompts the best builders already run on repeat. Steal all 7: