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
2) experiments to figure out best practices (which involves failure)
TOOLS
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Reconstructing Software Engineering for AI-Driven Coding
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2026 budget spent early not notable due to unknown Claude Code in 2025
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I don't think "we spent our 2026 budget in 4 months" is particularly notable given that the budget would have been set in 2025 when nobody knew how good Claude Code et al were about to get as-of January
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OpenAI Codex introduces Side Conversions in ChatGPT for side questions
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OPENAI : Codex in ChatGPT now supports Side Conversions, allowing users to ask side questions without disrupting the main thread. /Side testing
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System built with Codex due to Claude’s mistakes
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nah, it’s built with codex. Claude makes too many mistakes.
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Deep Agents v0.6 Enhances Harness Profiles for Cost-Effective AI Model Performance
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Deep Agents v0.6 makes harness profiles a first-class abstraction. Now, you can get production-grade performance from models like @Kimi_Moonshot
, @Alibaba_Qwen
, and @DeepSeek_ai at 20x+ lower cost than closed frontier APIs. More on tuning: -
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:
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Scoped Tool Access for AI Agent Control
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Scoped tool access keeps AI agents focused. Build custom tools defining exactly which historian data an agent can request and which parameters it can use. Everything outside stays invisible. Partner content with @HighbyteInc. #highbyte_iiot pic.twitter.com/GywTVbJa9k
— Lucian Fogoros (@fogoros) 29 mai 2026Scoped tool access keeps AI agents focused. Build custom tools defining exactly which historian data an agent can request and which parameters it can use. Everything outside stays invisible. Partner content with @HighbyteInc
. #highbyte_iiot