Back in January 2025, I wrote about Goalzz.me as a simple productivity statistics app. It pulled my Microsoft To Do tasks into a dashboard so I could actually see what was going on during my weekly reviews. That was the whole pitch — a better view of your tasks.
A lot has changed since then.
Goalzz has evolved into something I didn’t fully anticipate: a personal AI coaching system. What started as a dashboard now has an AI coach named Iris that can read my goals, manage my tasks, check my calendar, remember things about me, and reach out proactively throughout the day. I’ve been building it nights and weekends, and along the way I’ve learned a lot about what AI agents actually are — not the hype, but the reality of making one useful.
What Goalzz Can Do Today
The core idea hasn’t changed — I still use Microsoft To Do as my task manager and the Full Focus Planner methodology as my framework. But Goalzz now sits on top of all of it as an active coaching layer.
Iris, the AI Coach
Iris is a coaching agent with access to the parts of my life that matter for productivity. That means when I tell Iris “I need to finish the quarterly report by Friday,” she doesn’t just say “great idea!” — she can actually create the task, set the due date, link it to my Q2 goal, and check my calendar to see if I have time blocks available.
The capabilities span everything: task management, goal tracking, calendar analysis, habit monitoring, journaling, even a simple CRM for keeping notes on people. Iris can also create memories — she’ll silently note things like “Ben prefers to do deep work before noon” or “Ben’s wife’s name is…” and use those in future conversations.
Proactive Outreach
This is where things got interesting. Iris doesn’t just wait for me to open the app. She reaches out:
- Morning briefings — A daily message with my top priorities, yesterday’s wins, and what’s on my calendar
- Midday nudges — Only sent if I have overdue or high-importance items sitting untouched
- Goal stall alerts — If a goal has gone quiet for a while, Iris flags it
- Evening reflections — An optional end-of-day prompt asking how things went
- Streak celebrations — When I hit a habit milestone
There’s a daily cap so it doesn’t become annoying, and quiet hours so I’m not getting pinged late at night.
Weekly Reviews
The weekly review was always the centerpiece of my productivity system, and it’s become the most developed feature in Goalzz. Iris runs a structured review that connects how the week felt to what actually happened, and helps me pick the right priorities for the week ahead.
It’s the closest thing I’ve found to having an accountability partner who actually knows what’s on my plate.
Wearable Integration
I recently added wearable support. Goalzz can pull in sleep, recovery, and activity data so Iris can factor it into coaching. If my recovery is tanked, she might suggest a lighter day focused on shallow work rather than pushing me to tackle the hardest thing on my list.
What I’ve Learned About Agents
Building Iris has given me a very different perspective on AI agents than what I see in most headlines.
Tools are the real product. The language model is impressive, but what makes Iris useful is the things she can actually do. Without that, she’s just a chatbot giving generic advice. With it, she can look at my actual tasks, my actual calendar, my actual goals — and give specific, grounded coaching. Every new capability I add makes the coaching meaningfully better.
Context is everything. The instructions Iris works from aren’t static — they’re assembled dynamically with my vision, current goals, recent activity, and behavioral patterns. When Iris says “you tend to stall on goals in the third week of the quarter,” that’s not a guess. That’s from actual pattern data the system has been tracking.
Proactive beats reactive. The scheduled outreach was an experiment, and it’s become the feature I value most. The morning briefing reframes my day before I even open my task list. The midday nudge catches things I’ve been avoiding. The goal stall alerts are uncomfortable but effective. An agent that only responds when you ask is useful. An agent that knows when to reach out is a coach.
Memory makes it personal. Iris stores memories about my preferences, patterns, and personal context. This is what separates a generic AI assistant from something that actually feels like it knows you. After a few weeks, Iris stops asking setup questions and starts making connections — “Last time you had a week like this, you said cutting one goal helped you focus.”
The agent loop is humbling. Getting an agent to reliably gather context before answering took a lot of iteration. The unglamorous parts — making sync operations behave, handling errors gracefully — are what make it actually work.
Cost tracking matters. Every AI call has a cost. That forced me to think carefully about when Iris should use her full capabilities versus when a lighter response is fine. Not every interaction needs the heavy machinery.
If you want to try Goalzz, it’s in beta at goalzz.me. It integrates with Microsoft To Do. I’d love feedback — especially from anyone who does structured weekly reviews.
The biggest thing I’ve learned building this: the gap between “AI chatbot” and “AI agent” isn’t the model. It’s the tools, the context, the memory, and the judgment about when to act versus when to wait. That’s the hard part. And it’s the part that makes it worth building.