The importance of context in a product team

Ever feel like the team is replaying the same conversation across three apps? A designer nudges a token. The spec forgets to mention it. The ticket omits the why. The PR arrives and QA spots a mismatch.

Was the spacing updated? Which variant moved? Who decided and when? If these questions sound familiar, the issue is not motivation. It is missing context at the moment of work.

Where time really disappears

Small gaps compound into detours that nobody planned for. A variant name changes, yet the link inside the issue still points to an older node, so a developer implements the right idea against the wrong source.

A product manager rewrites a ticket to help a second audience, and without meaning to, creates a parallel narrative that drifts away from the original decision. A reviewer approves a screenshot in chat rather than the live frame, and signs off on something that no longer exists.

Each moment looks harmless in isolation. Together they stretch a sprint, nudge estimates upward, and force people to reconfirm details that should have traveled with the change.

A practical test helps. Can a teammate, including someone new to the project, open a single place, see the exact diff, understand the intent, and know the next step without asking for a meeting?

Tool sprawl from a design vantage point

Design is one window into product reality. Conversations unfold in Slack, work moves through Linear or Jira, code evolves in GitHub, and evidence lives in Amplitude and Maze. A modern product is not just an interface or a block of code. In a SaaS or an app, it is user insights, business data, code, the team, the documentation, and the decisions that connect them.

When these systems do not share a language, the chain from decision to design to code breaks exactly when you need it to hold. Threads drift into the archive, screenshots lose context, dashboards hint at impact without pointing back to the specific node or the precise pull request, and people rely on memory to fill the gaps. Reviews slow down, releases become timid, and attention is taxed by repeated explanations that should not be necessary.

The shape of useful context across the stack

Useful context is compact, specific, and available at the moment of action. For every change, three answers should be easy to find in one place people already use.

• What changed, with a stable link to the exact node or component, so there is no confusion about which variant or mode is in scope.

• Why it changed, with the intended impact stated clearly, and a pointer to evidence when it exists, such as an Amplitude chart or a Maze study.

• What happens next, with ownership, status, and acceptance criteria short enough to scan, so the next person can move without asking for another clarification.

When those answers live together, alignment becomes a property of the workflow, not a meeting to schedule. People decide faster because intent and boundaries sit beside the work. QA references the same source as engineering. Documentation links back to the artifact that justified the decision. Leadership can read the narrative without asking for a separate summary.

How MCP helps without covering the entire journey

Figma’s Model Context Protocol gives agents and IDEs access to design context with higher fidelity. Less guessing, better translation from frames to code, and more trustworthy assisted workflows follow from that foundation.

You can generate code with fewer mismatches, reason about states and tokens with more confidence, and move routine changes forward without rewriting a long specification.

MCP strengthens the bridge from design to implementation. It does not, on its own, coordinate the full journey from a design edit to an actionable ticket, a thoughtful review, a clean pull request, the documentation that codifies the decision, and the analytics that confirm outcomes later.

Keeping the story close to where work happens

If you want rails that respect your current habits, Lyse observes Figma for component, token, and rule changes, then turns those events into context rich tasks in Linear, GitHub, or Jira.

Each task carries the diff, the rationale, and clear acceptance criteria, so work moves from change to review to pull request with fewer back and forths.

MCP improves fidelity from design to code, and Lyse keeps the story intact across the workflow, while leaving space to attach analytics and research so the design perspective scales to the entire product team.