Sign in
Skip to solution
mediumAI Engineering

What is the ReAct pattern and why did it become the default for agents?

67 views
01

Understand the problem

Interleaving reasoning and acting: thought, action, observation on repeat.

react-patternagentsreasoning
02

Attempt it yourself

Sketch your approach before reading the solution — that's what interviews test.

Nudge consolestandby

Stuck? Beam a request up — the console returns a conceptual nudge that guides your logic without spoiling the implementation.

03

Study the solution

ReAct (Reason + Act) has the model alternate explicit reasoning steps ('the user wants X, I should check Y') with tool actions, feeding each observation back before the next thought. The verbalized reasoning improves action selection and makes trajectories debuggable — you can see why the agent chose a tool. Modern too

Solution ready — 2 min read

Classified // press E to declassify

04

Read the code

A ReAct trajectory (what you read when debugging)
Thought: The user asks for Q2 refunds for customer 811. I need order data first.
Action:  search_orders({ customer_id: "811", from_date: "2026-04-01",
                         to_date: "2026-06-30", status: "returned" })
Observation: 3 returned orders: #90312 ($120), #90417 ($60), #90583 ($75)

Thought: Refund totals come from the payments tool, not order totals.
Action:  get_refunds({ order_ids: ["90312", "90417", "90583"] })
Observation: refunds: 90312=$120, 90417=$60, 90583=$0 (pending)

Thought: Two completed refunds ($180), one pending. I can answer precisely.
Final:   "Q2 2026: $180 refunded across 2 orders; 1 refund ($75) still pending."
05

Join the discussion

Discussion (0)

Sign in to join the discussion.

No responses yet. Be the first to share what you think.

Transmission complete // awaiting log

KEEP THE
STREAK ALIVE.

Dossier 56 of 80 decoded in the AI Engineering track. One more won't hurt.

Back to track