2026State of
Agentic
Coding
The tools are changing.
So is the way we make software.
The quality of the work depends on how these pieces fit together.
01 / A new working relationship
UNDERSTANDFrom asking for code
to delegating work.
An agent can inspect a project, make changes, run tools, and use the results to decide what to do next. That loop is the important part.
You describe an outcome.
The system takes steps.
You need evidence.
This opens up more than faster typing: understanding unfamiliar systems, turning ideas into working prototypes, implementing bounded features, and investigating failures.
TRY THE THREE MODES ↑
These modes overlap. An agent may pause for input; an editor assistant may run tools. Look at what the configured system can actually do, and what it is allowed to change.
02 / Untangle the vocabulary
UNDERSTANDSame model.
Different experience.
The model is one ingredient. The surrounding software decides what it sees, which tools it can use, and how its work reaches your team.
Choosing Claude inside another product does not automatically give you the Claude Code workflow.
03 / Make it concrete
UNDERSTANDOne feature.
An entire workflow.
Imagine a checkout that gives confusing feedback after a connection problem. Your team wants to fix the experience without changing how payments work.
This is a fictional example, not a live agent run. The critical decision: an unresolved payment status must stay unresolved until the existing server contract establishes what happened.
Build a task brief ↗04 / Capability meets consequence
EXPLOREWhat would you
trust it with?
Start with work you can describe and verify. Increase autonomy when the task, environment, and evidence justify it.
Understand & explore
Map a user flow. Explain an unfamiliar module. Build a disposable prototype. Draft tests from acceptance examples.
Implement & improve
Fix a reproducible bug. Add a feature in an existing pattern. Refactor a module. Build UI states against an agreed API.
Change systems people depend on
Permissions, payments, data migrations, shared infrastructure, or any change with a difficult recovery path.
Jay’s guidance: delegate a coherent outcome, then judge the delivered behavior. These are suggested task classes, not guarantees of what every model or product can complete.
05 / Find your starting point
EXPLOREMeet the systems.
Some package the whole experience. Others give you parts to assemble. Choose for the way your team works, then test on your own projects.
CLI = a terminal interface. IDE = an editor with development tools. A product’s model choices, subscription access, API billing, and cloud-compute charges can differ.
As of 27 October 2026. Categories are navigation aids and can overlap. Mobile often means remote control; the detail view explains where tools execute. “Best fit” is a practical assessment, not a measured ranking.
06 / Evidence, with context
EXPLOREA score is a clue.
Read the conditions.
A terminal task, a repository fix, and a whole-program reconstruction test different things. Each view below answers a different question.
Hold the system steady.
Use the same harness, tools, task, and budget. Record exact model versions and reasoning settings.
Test its real workflow.
Let each product use its documented setup. Record differences in context, tools, retries, and access.
Count accepted outcomes.
Include setup, supervision, review, integration, cost, and defects. Measure the team’s complete effort.
Published results, not hands-on tests conducted for this guide. Do not combine these percentages into one universal ranking. Model aliases, versions, and product availability change quickly.
07 / Interface ≠ execution
EXPLOREWork from anywhere.
Know where it runs.
Your screen, the machine changing files, and the model service can be in three different places. That matters for convenience, control, and data.
Useful for servers, containers, and repeatable jobs. The selected harness still determines its controls.
A broad local and desktop ecosystem. Remote sessions need the host to remain available.
Native tools and Windows Subsystem for Linux (WSL) coexist. Check each tool’s sandbox and command compatibility.
Mostly a place to direct work elsewhere. Pi on Android through Termux is a documented local CLI exception.
A delivery surface, not an operating system. A browser can reach a local server or a cloud workspace.
Open source, self-hosted execution, and local model inference describe different layers. Verify the actual data path rather than assuming one implies the others.
08 / Coordinate the work
PUT IT TO WORKMore agents need
more ownership.
Parallel work helps when tasks are separable. It also creates handoffs, conflicting assumptions, and an integration job someone must own.
Start with one accountable path.
Give each concurrent writer a bounded task and a separate checkout. Have one person or principal agent own the combined result and the evidence needed to accept it.
- Separate edits. A worktree helps avoid file collisions.
- Separate authority when needed. A worktree alone does not isolate processes or credentials.
- Check the integrated result. Two passing branches can still behave badly together.
Bounded feature change
Tests, inspection, challenge
Suggested operating pattern. A separate agent conversation is not automatically a security boundary, and a detached terminal is not a recovery plan for a machine restart.
09 / Find your contribution
PUT IT TO WORKMore making.
More judgment.
Agents can help more people turn ideas into something tangible. Every role still brings decisions the system cannot settle on the team’s behalf.
Suggested workflows, not predictions about job titles. If you’re new, ask the agent to map an existing flow and identify unknowns before authorizing changes.
Build a team plan ↗10 / The acceptance problem
PUT IT TO WORKReview is moving.
Responsibility stays.
Some teams have shown workflows with little human line-by-line review. They rely on substantial evaluation and operating discipline. That is a direction to investigate, not a default policy for every team.
The question becomes:
“What evidence lets us accept this change?”
Code inspection remains one useful tool. Add behavior, accessibility, system invariants, integration checks, and what happens after release.
Define success.
Use observable acceptance examples and state what must remain true.
Test the change.
Protect important checks. Ask what the implementation might have missed.
Accept the result.
Inspect consequential paths. Match review effort to uncertainty and impact.
Watch what happens.
Use staged releases, monitoring, ownership, and practical recovery paths.
Does using an agent automatically make a team faster?
No universal causal result establishes that. METR’s early-2025 randomized study of experienced open-source developers found a slowdown in that setting. Its 2026 follow-up explained why a clean updated estimate was difficult; later self-reported gains answer a different question. Measure your own accepted changes, including review and rework.
Why isn’t a passing test suite enough?
Tests reflect the behaviors they check. Maintainer studies have found benchmark-passing patches that still would not be accepted. Ask whether the change solves the right problem, fits the system, handles important edge cases, and is maintainable. Those studies use bounded samples, not a universal failure rate for today’s tools.
Suggested risk-based policy. Removing a human gate should follow evidence for a task class, with protected checks and accountable recovery.
11 / Set the work up well
PUT IT TO WORKGive the agent
a working system.
Good instructions help. A reliable environment, relevant context, effective limits, and truthful completion evidence make the workflow repeatable.
A brief for this task
Describe the user outcome, scope, acceptance examples, and decisions that need a person. Make the handoff explicit.
Repository guidance for this project
Keep build commands, conventions, and invariants close to the code. Formats such as AGENTS.md help make guidance discoverable.
Stable facts belong here. Temporary decisions belong in the task.Skills for repeatable procedures
Package a recurring process with instructions, examples, and supporting scripts. Evaluate it on fresh tasks and retire stale guidance.
Tools and connections for useful access
Model Context Protocol (MCP) connects tools and resources. Agent Client Protocol (ACP) connects coding agents to editors and other clients. Add the access the work needs, and inspect what each integration can do.
Enforced controls for real boundaries
Use scoped credentials, execution isolation, permission policies, and release controls. Verify coverage across shell tools, plugins, and delegated agents.
Make the ask concrete.
Choose a starting point, then adapt it to your product.
Briefs and suggested practices are Jay’s synthesis. Check the selected harness’s instruction rules and the effective permissions of every tool path.
12 / Build the conditions to scale
PUT IT TO WORKStart small.
Make it repeatable.
A suggested 30 / 60 / 90-day sequence. Move forward when the evidence is good enough, not because the calendar says it’s time.
Did the task meet the agreed criteria?
Include setup, steering, review, and rework.
Count every attempt, tool, and human hour.
Track what escaped and the effort to recover.
The checklist is a planning aid, not a validated readiness score. Keep a shared team record if you need collaboration across people or devices.
13 / The longer view
TAKE IT FORWARDThe durable advantage is
a better way of
working.
Describe what good means.
Turn user needs into observable outcomes, constraints, and examples. Better specification helps every model and every teammate.
Build a system agents can use.
Keep setup reproducible, knowledge findable, tasks bounded, and ownership explicit. Treat the environment as part of the product.
Earn the next level of autonomy.
Learn from failures, protect critical checks, and measure accepted work. Expand where your workflow proves dependable.
Product · Experience · AI / jsethi.com
Forward-looking guidance and synthesis. The products will keep changing; use the underlying questions to update your decisions.
14 / Keep exploring
REFERENCEA guide you can
come back to.
Use the glossary when the vocabulary gets dense. Follow the sources when a product claim or benchmark affects a decision.
Grounded in the research.
Adapted from Jay Sethi’s detailed findings report. It draws on official documentation, original benchmark results, research papers, and first-hand engineering accounts checked for the 27 October 2026 snapshot.
Published scores belong to their evaluators. This guide does not claim a hands-on comparative test. The examples, suggested workflows, and adaptation plan are synthesis, not vendor guarantees.
A self-contained HTML edition. No account, analytics, or runtime downloads. Theme, reading position, and checklist choices stay in this browser when storage is available. A printed copy includes the currently selected interactive views.