Happy Triple Threat Thursday.
Here’s one Signal to notice, one thing to Spark growth and one Shift to consider.
This week's theme: Agents are real. The autonomy isn't.
By now you've heard the hype. Agents. AI coworkers. Claude replacing teams. Autonomous systems running your workflows. It's loud. If it feels overwhelming, that's normal.
Claude coworker is impressive. Long context is strong. Structured reasoning is solid. In certain use cases it does feel ahead of standard chat interfaces. But it cannot replace your inbound engine. It cannot run your outbound system end to end. And you are not behind.
Most of what you're seeing assumes reliable autonomy. That part isn't here yet.
📡 Signal — What’s Changing
The Shift from Chat to Configuration
The change isn't just smarter responses. It's structure.
Claude's coworker model introduces Projects, Skills, persistent instructions, and stored context. That matters. What hasn't changed is that AI still struggles with ambiguity. If the task isn't tightly defined, if inputs are inconsistent, if no one has decided what "done" means, performance drops quickly.
The model usually isn't the problem. Scope is.
Agents perform well inside clear boundaries. Outside of that they drift. You don't need to panic about any of this. You need structure.
Takeaway: The technology is improving fast. It still depends on the clarity you provide.
⚡ Spark — What to Try This Week
How to Configure Claude Coworker Correctly
Don't start with a system. Start with one task. Something repeatable, bounded, something you already do every week.
Turning meeting transcripts into structured action lists. Turning a sales call transcript into a deal brief with next steps and risk flags. Reviewing a vendor proposal against your standard contract terms and flagging anything that doesn't fit. Pulling weekly pipeline data into a concise summary with the three things that need your attention.
Not "create my marketing strategy." Not "find me qualified prospects on LinkedIn." One narrow, specific, defined job.
Step 1: Create a Project. Projects hold context and memory. Inside the Project define what triggers the work, what input it receives, what the output must look like, and what it is not allowed to decide. Be specific. Literal instructions outperform clever prompts every time.
Step 2: Understand Projects vs Skills. Projects store the job and its reference materials. Skills enforce repeatable behaviors, formatting rules, extraction patterns, guardrails. Projects hold the environment. Skills control the execution. Skip this distinction and results will feel inconsistent.
Step 3: Define the human handoff. Every AI coworker needs escalation rules. What requires review. What cannot be sent without approval. What uncertainty should be flagged. Agents are fast. They are not accountable.
For the best output, write your instructions in plain language first: exactly how you'd explain the task to a new hire. Then run it through the Leadway Prompt Engineer. It takes what you wrote and turns it into a structured, high-quality prompt you can drop straight into Claude Projects or Skills. Yes, it's built in ChatGPT. It works with Claude and other models. Strong configuration beats clever prompting every time.
Takeaway: Start narrow. Configure clearly. Expand only after it performs reliably.
🔄 Shift — How to Rethink It
Agents Rewrite Tasks. They Don't Replace Roles.
The online narrative says agents replace jobs. What's actually happening is simpler. They rewrite tasks.
The reliable wins right now come from structured, low-variance work with clear inputs and predictable outputs. Autonomy still struggles with messy, multi-step, high-judgment processes. That will improve. It is not there yet.
Treat an agent like a junior analyst with a tight job description and it performs well. Treat it like an executive and it disappoints.
You are not behind. You just need discipline.
Takeaway: Build one useful AI coworker before you try to build an AI workforce.
📚 Worth A Look
🔗 Claude Cowork’s role in productivity and collaboration
This report examines how Claude Cowork is being used to support workflow execution across functions like operations and HR, illustrating current strengths and practical uses of agentic AI in real work contexts.
🔗 Claude Cowork: Desktop AI agent guide
A recent practical guide explains how Claude Cowork functions as an autonomous desktop agent, managing files, executing multi-step workflows, and interacting with external services, which highlights both the potential and the risks of giving agents real access to your work environment.
🔗 AI Agents in 2026: How businesses will use them differently
This piece explores how AI agents are evolving from experimental tools into parts of daily workflows, driven by improvements in context handling and reasoning, but also shows why most organizations use them for narrow tasks first.
📈 TL;DR
Claude coworker is powerful for tightly scoped work. It cannot replace your revenue systems yet. Configure carefully. Start small. Expand slowly.
📈 One Question
What is one clearly defined task you could confidently hand to an AI today?
Thanks for reading Triple Threat. See you next Thursday with another Signal, Spark, and Shift.
— Alexandria Ohlinger
p.s. If this helped you think sharper or move faster, share it with someone who builds the way you do. And if you want more practical insight between issues, connect with me on LinkedIn.