# Releezy > Releezy is an AI development suite for engineering teams and their leaders. It brings together product discovery, agent orchestration, code review and engineering measurement. The company is Releezy Corp. Releezy Guardian, Releezy Loop, Releezy Reviewer and Releezy Plan are the four core product modules. English pages use the root paths. Portuguese pages use /pt/. Blog links below provide the published Markdown source; each article links to its canonical web page. ## Product and services - [Releezy suite](https://releezy.com/releezy) - [Releezy Guardian — Evidence for engineering leadership](https://releezy.com/guardian): Understand development flow, review effectiveness and code durability. Data to improve the work of people and AI. - [Releezy Concierge — From evidence to the next action](https://releezy.com/concierge): Discuss engineering data and find next steps to improve development with people and AI. - [Releezy Plan — Clarity before building](https://releezy.com/plan): Explore the problem, question assumptions and organize scope before committing the team to implementation. - [Releezy Loop — AI execution under control](https://releezy.com/loop): Coordinate coding agents with project context, isolated environments, spending limits and run visibility. - [Releezy Reviewer — Project criteria in every review](https://releezy.com/reviewer): Deepen review with specialized agents and contextual PR findings. Project criteria to guide the team’s assessment. - [Releezy Advisor — Prepare your codebase for AI](https://releezy.com/advisor): Identify context, documentation and validation gaps that make agent work harder in your repository. ## Leadership perspectives - [Releezy for CEO](https://releezy.com/for-ceos) - [Releezy for CFO](https://releezy.com/for-cfos) - [Releezy for CTO](https://releezy.com/for-ctos) - [Releezy for Tech Lead](https://releezy.com/for-tech-leads) ## Resources and applications - [Methodology](https://releezy.com/methodology): Understand how Releezy Guardian turns development history into evidence to assess reviews, quality and team progress. - [How it works](https://releezy.com/how-it-works): Explore the Releezy adoption path: choose a project, read its history with Guardian and guide the team’s next improvement. - [Explore the product](https://releezy.com/product): Explore the questions Releezy Guardian helps answer about reviews, AI tools and progress in software development. - [Build vs. buy](https://releezy.com/build-vs-buy): Assess the responsibilities of building a measurement solution or adopting Releezy: integrations, methodology and continuity. - [Engineering visibility](https://releezy.com/engineering-visibility): Find waiting time, concentrated review load and code durability signals to decide where to improve delivery with Releezy Guardian. - [AI impact in engineering](https://releezy.com/ai-impact-measurement): Evaluate contributions and reviews by agents identified in repository records, follow durability and decide how to evolve AI adoption. - [AI adoption with execution controls](https://releezy.com/safe-ai-adoption): Define scope, review and spending limits for agent adoption with Releezy Loop, Releezy Reviewer and Releezy Guardian. - [Code review effectiveness](https://releezy.com/code-review-effectiveness): Follow review comments and subsequent commits to the same file. Use Releezy Guardian signals to adjust review focus and criteria. ## Company - [About the company](https://releezy.com/about): Meet Releezy Corp, the company building the Releezy suite, and the principles behind our work. - [Trust and responsibilities](https://releezy.com/trust): Understand the access, actions, and responsibilities of each Releezy module. - [Contact Releezy](https://releezy.com/contact) ## Articles — English - [The AI Adoption Spectrum and the 6x Gap](https://releezy.com/blog/ai-adoption-spectrum.md): OpenAI data from 9,000 workers shows a 6x productivity gap. It is a spectrum to climb, not a binary to flip. Here is what that means for your team. - [The Benchmark Paradox in AI Code Review](https://releezy.com/blog/ai-code-review-benchmark-paradox.md): Vendor benchmarks report 60% F1. Academic tests show 19%. What the 3x gap means for teams measuring AI code review effectiveness. - [Code Review Is Not Dead. It Is Becoming Governance.](https://releezy.com/blog/code-review-is-not-dead.md): Why review layers survive AI speed. What data from 10,000 developers and the 75% evolvability finding reveal about code review in the age of AI agents. - [Fast to Generate, Slow to Trust: The 1:24 Ratio](https://releezy.com/blog/fast-to-generate-slow-to-trust.md): One AI rewrite took 7 hours to generate and a week to verify. What the 1:24 ratio reveals about trust and where engineering teams should invest. - [Measure the Team, Not the Model](https://releezy.com/blog/measure-the-team-not-the-model.md): Coding agents excel when a human steers them. Discover why measuring the human plus agent pair, not the model, is how teams build trust in AI. - [Two Ways to Measure AI Adoption, Both Broken](https://releezy.com/blog/measuring-ai-adoption-without-surveillance.md): Peer stigma and token surveillance both break AI adoption numbers. What a trustworthy, team-level way to measure AI at work looks like. - [Measuring AI in Software Development](https://releezy.com/blog/measuring-ai-software-development.md): What a randomized trial and data from 600+ organizations reveal about measuring the real impact of AI on software teams. - [The Trust Gap Is the Governance Gap](https://releezy.com/blog/trust-gap-governance-gap.md): 84% of developers use AI coding tools. Only 33% trust the output. The trust gap now has a measurable number, and measuring it is how teams close it. ## Artigos — Português - [O Espectro da Adoção de IA e o Gap de 6x](https://releezy.com/pt/blog/ai-adoption-spectrum.md): Dados da OpenAI com 9.000 trabalhadores mostram um gap de 6x. A adoção de IA é um espectro para subir, não um binário para virar. Veja o que isso muda. - [O Paradoxo do Benchmark no Code Review com IA](https://releezy.com/pt/blog/ai-code-review-benchmark-paradox.md): Benchmarks de vendors reportam F1 de 60%. Testes acadêmicos mostram 19%. O que a lacuna de 3x significa para medir code review com IA. - [Code Review Não Morreu. Está Virando Governança.](https://releezy.com/pt/blog/code-review-is-not-dead.md): Por que camadas de revisão sobrevivem à velocidade da IA. O que dados de 10 mil desenvolvedores e o achado de 75% de evoluibilidade revelam. - [Rápido para Gerar, Lento para Confiar: a Proporção 1:24](https://releezy.com/pt/blog/fast-to-generate-slow-to-trust.md): Uma reescrita com IA levou 7 horas para gerar e uma semana para verificar. O que a proporção 1:24 revela sobre confiança e onde os times devem investir. - [Meça o Time, Não o Modelo](https://releezy.com/pt/blog/measure-the-team-not-the-model.md): Agentes de código brilham quando um humano os direciona. Descubra por que medir o par humano mais agente, e não o modelo, constrói confiança no time. - [Duas Formas de Medir Adoção de IA, Ambas Quebradas](https://releezy.com/pt/blog/measuring-ai-adoption-without-surveillance.md): Estigma entre colegas e vigilância de tokens quebram os números de adoção de IA. Como medir IA no trabalho de um jeito confiável, no nível do time. - [Medindo IA no Desenvolvimento de Software](https://releezy.com/pt/blog/measuring-ai-software-development.md): O que um estudo randomizado e dados de mais de 600 organizações revelam sobre medir o impacto real da IA em times de software. - [A Lacuna de Confiança É a Lacuna de Governança](https://releezy.com/pt/blog/trust-gap-governance-gap.md): 84% dos desenvolvedores usam IA. Só 33% confiam no resultado. A lacuna de confiança tem um número mensurável, e medir é o caminho para fechá-la. ## Optional - [Releezy em português](https://releezy.com/pt/) - [All public pages and language variants](https://releezy.com/sitemap.xml) - [English blog RSS](https://releezy.com/rss.xml) - [Blog em português — RSS](https://releezy.com/pt/rss.xml)