Topic
Software development approach that encodes requirements and tasks as version-controlled specs for AI coding agents to execute, instead of prompting.
Relipa's AI development workflow wraps a coding agent in six stages and fixes the tests before any code is written. Most of its published detail covers the workspace plumbing that runs before a model is ever called.
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System Design One's newsletter says AI agents on big codebases need written specs, citing a change that passed tests but emailed an opted-out user. Most of its sample spec just records what the old system already does, and a team can write that document before buying any agent platform.
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One operator ran spec-driven development at full BMAD weight for four weeks on an autonomous coding repo. The planning stage produced 1,782 files and 16 MB of artifacts, and a single story burned around thirty million tokens.
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A dev.to writeup wires CPU and RAM telemetry from a Manifest V3 extension down to a standalone Windows binary. The first of its seven written rules: nothing may print to stdout, where Chrome expects a 4-byte length prefix.
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A dev.to post groups spec-driven development frameworks by what they do with the markdown once the LLM has written the code, and argues for deleting it on the grounds that code is the less ambiguous description.
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For the first ninety minutes nobody opens an IDE. A mentor has to approve the team's SPEC.md, and that same file is what Antigravity or Cursor reads once the coding starts. It is worth 35 of the 100 points.
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Offset paging passes a static test suite and then skips rows the moment a merchant inserts a product mid-read. A dev.to case study answers that by freezing the sort key, tie-breaker and error codes in a spec file the agent cannot edit.
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A month and a half of prototyping an experimental functional language with Codex ended with eight artifacts around the repository and a documentation flow in which ChatGPT writes the prompts and Codex writes the spec.
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Signadot's argument is that the bill for an unattended coding loop is the iterations it needs times the cost of each one, and that only feedback precise enough to localize a fault shrinks both of those terms at once.
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Anthropic's playbook says code is no longer the bottleneck, and the spec-driven tools around it each prescribe one fixed sequence of stages. The New Stack argues the process should be data an organization defines itself.
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SWC's creator fanned a single instruction out to 45 concurrent Labor0 tasks on the ES minifier, then kept review and merge for himself. He says he does not know how long the run took; he was looking at his phone.
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A study accepted at GAISS 2026 reports that a specification baseline increased the attributability of reviewers' bug finds without increasing their count, and that on easy tasks the credit for spec-first prompting mostly belongs to reasoning effort.
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Enforcement is a bash script that counts files against the merge-base with the parent branch, so it bounds one diff at a time, and only if the agent chooses to run it. The 100 is an environment variable's default.
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The enforcement is a bootstrap prompt the agent checks before every task, so its durability depends on per-harness plumbing. On Hermes Agent, compaction can lose it.
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Daniel Vaughn's experimental editor treats pseudocode as the durable artifact and generated source as output. The public build sends the whole spec to a model and shows read-only code.
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Salesforce says builds, tests and reviews validate the diff, not the requirement. Its answer was a specification gate upstream of the code, plus a rule about which questions agents may answer.
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A dev.to writeup argues long sessions degrade structurally, not linguistically, and proposes research/plan/implement phases with a hard context clear between each.
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A dev.to comparison of OpenSpec and GitHub Spec Kit argues chat degradation is structural. The interesting part is not the diagnosis but how differently the two tools file the cure.
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