7 min read
Every Agentforce build eventually asks the same question: should the agent reason step by step as it goes, or plan the whole task up front? ReAct and Plan-and-Execute are the two dominant answers, and picking wrong shows up fast in cost, latency, and reliability. Most teams pick based on habit rather than the actual shape of the task, and it costs them later.
Every Agentforce build eventually asks the same question: should the agent reason step by step as it goes, or plan the whole task up front? ReAct and Plan-and-Execute are the two dominant answers, and picking wrong shows up fast in cost, latency, and reliability. Most teams pick based on habit rather than the actual shape of the task, and it costs them later.
Two Ways to Loop
ReAct interleaves reasoning and action in a single loop: the agent thinks, calls a tool, observes the result, and decides the next step based on what it just saw. Plan-and-Execute flips the order. The agent builds a full plan graph first, then works through each step, only revisiting the plan when a step fails. One loop adapts turn by turn. The other commits to a shape before it moves.
The tradeoff is not just architectural, it shows up directly in behavior. A ReAct agent can get stuck in unproductive loops when a tool returns an ambiguous result, repeatedly trying slightly different queries without making progress. A Plan-and-Execute agent can commit to a plan that was reasonable at the start but wrong given what step three actually returned, and keep executing it anyway unless the orchestration explicitly checks for that.
What This Looks Like in Practice
Picture a support agent looking up a customer's order status. With ReAct, the agent calls a lookup, sees the order is delayed, and decides in that moment whether to check shipping carrier status next or draft an apology message, based on what it actually found. With Plan-and-Execute, the agent would have already decided, before making any calls, that step two is checking shipping carrier status regardless of what step one returns. If the order was not delayed at all, that plan is now doing unnecessary work.
When Each Wins in Agentforce
ReAct fits work where the next move genuinely depends on what a tool returns: troubleshooting a case, searching across records with an uncertain path to the answer, or any topic where the right action only becomes clear mid-conversation. Plan-and-Execute fits well-defined business processes: approvals, provisioning, multi-step data updates, anything where reviewers want to see the plan before execution starts. It also front-loads the reasoning cost into one planning pass instead of paying for it on every turn, which matters once you are running thousands of sessions a day.
The Hybrid Pattern We Reach for Most Often
In practice, the agents we ship rarely pick one loop for everything. A topic that provisions a new account might use Plan-and-Execute for the core steps, since the process is well understood and auditable, while falling back to a ReAct-style exception handler when a step fails in a way the plan did not anticipate. The planning layer gives you predictability. The reactive layer gives you a way out when reality does not match the plan.
Conclusion
Neither loop is universally better. Match the loop to the shape of the task: reason as you go when the path is genuinely unknown, plan up front when the process is defined and needs to be inspectable. Most production Agentforce agents end up using both, at different topics within the same agent.
If you are deciding for a new topic and genuinely unsure, ask whether a reviewer would want to see the plan before it runs. If yes, start with Plan-and-Execute. If the honest answer is that the plan cannot be known until the agent sees the data, start with ReAct and add guardrails against unproductive loops from day one.