From Vibe Codingto Agentic Engineering.

    Engineering is 80% judgment and process, 20% code. AdaL operationalizes the whole process through agents.

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    Agentic Engineering ForHigh-Performing Teams

    AdaL combines high-precision Worker Agents for research, coding, browser use, verification, and review with Engineer Agents that automate the workflow and share long-term memory with humans, so teams focus on the decisions that matter most.

    › curl -fsSL https://adal.sylph.ai/install.sh | bash

    Download the Desktop app for macOS Apple Silicon & Intel.

    Trusted by engineers from

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    Our Thesis

    The vibe coding crisis is real.

    The vibe coding crisis is not that AI writes bad code. It is that teams confuse code generation with engineering progress.

    Code was only the visible 20% of engineering. The other 80% was understanding the problem, planning architecture, making tradeoffs, reviewing decisions, debugging edge cases, and maintaining quality.

    Agentic engineering brings that 80% back into the workflow. Agents execute with rigor, share long-term memory, and bring humans in for the decisions that shape the system.

    Designed For High-Trust Engineering Workflows.

    AdaL is not just built for agents to run in automode. It is designed so humans can follow the work, understand the reasoning, and precisely intervene when judgment matters — with one continuous session across the CLI, Agentic IDE, and specialized worker agents.

    CLIAgentic IDEWorker AgentsAgent Infra

    Move fast without losing the thread.

    AdaL CLI is built for fast autonomous work without becoming a black box: full chat history, visible tool inputs and outputs, reviewable steps, and instant model or worker-agent switching.

    /ideopen Agentic IDE in browser or desktop for visual tasks, PR review, and precise collaboration
    Learn more about AdaL CLI
    AdaL CLI
    Fix checkout rounding and add a regression test.
    Thought... [Ctrl+R to expand]
    ◐Inspect totals, reuse the money helper, then add a focused regression test.
    ▸ Deep Research Subagent · Inspect checkout total rounding bug[click to expand]
    ✔
    Edit (src/checkout/totals.ts)
    ⎿ @@ -42,2 +42,2 @@ calculateTotal
    42-const tax = subtotal * rate;
    42+const tax = roundMoney(subtotal * rate);
    43-return subtotal + tax + shipping;
    43+return roundMoney(subtotal + tax + shipping);
    ... [18 more lines] ...
    [click to expand]
    Modified (+42, -18).
    ✓
    Worker(Review · regression path)ready
    ⎿ checkout.totals passed — rounding edge case covered
    ◐Done. Fixed checkout rounding and added the regression test.
    Claude Opus 4.6 (64%)·Deep Research
    storefront (fix/checkout-rounding)
    YOLO

    Deepen Human Understanding and Agent Collaboration

    Agentic IDE is built for the moments where terminal output is not enough — helping engineers inspect source code, review visual tasks, understand clustered changes, and collaborate precisely with AdaL in the browser or native desktop workspace.

    Review Agent lives hereBrowser + desktopHuman-AdaL workflow
    Learn more about Agentic IDE
    adal
    ›Build something great or fun...↵
    Auto ▸Auto-Edits
    Coding ▸GPT-5.3 Codex ▸
    adal
    video-agent
    adalvideo-agent
    Review Cards
    3 clusters · 9 files
    Video Generation Pipeline
    high
    3 files+124−8
    Voice Synthesis
    medium
    2 files+67−4
    Agent Orchestration
    low
    4 files+92−12
    adal
    video-agent
    adalvideo-agent
    AGENTS.md
    PreviewSource

    adal Repository Guidelines

    If you are AdaL, this is source code, from your CLI to backend in deep_research, to tools, to AdaLFlow.

    Your goal is to self-evolve into the best coding, engineering, and research agent in the world.

    Your differentiators include:

    1. 1.simplicity UI/UX without adding too many buttons or frictions.
    2. 2.agentic-first approaches that start from first principles.
    3. 3.senior-engineer workflows that improve the product while doing the work.

    Project Structure & Module Organization

    adal-cli/ React terminal frontend; spawns the backend automatically.

    Delegate work across all frontier models.

    AdaL worker agents can run on Claude, GPT, Gemini, Kimi, DeepSeek, GLM, MiniMax, and more. Each worker brings the right model and toolchain into one agentic engineering workflow.

    Explore worker agents

    Deep Research directly from your codebase.

    report.mdcited memo
    # Checkout Rounding Analysis
    ## Findings
    - Repo uses mixed float math in totals
    - Existing helper: roundMoney()
    ## Recommendation
    Round tax and final total at the boundary.
    Learn more

    Plan, Code, Document Here.

    src/checkout/totals.ts
    42- subtotal * rate
    42+ roundMoney(...)
    ✓ npm test -- checkout.totals
    Learn more

    Operate the web with visible control.

    browser
    ✓ open checkout flow
    ✓ capture screenshot evidence
    Learn browser use

    Build Your Agents on Top of AdaL.

    Use AdaL headless, through the SDK, or with a meta-agent that helps harness domain-specific worker agents.

    Learn more
    HEADLESS
    Run agents in production
    Trigger AdaL from CI, background jobs, internal tools, and server workflows.
    SDK
    Compose custom workers
    Build domain agents with your tools, models, memory, prompts, and guardrails.
    META-AGENT
    Generate agent systems
    Use a meta-agent to scaffold roles, evals, workflows, and reusable worker patterns.