Field Report Day 2: 'I Didn't Think I Could, But I Did' — Building Real Workflows in One Day

Published: 2026-05-31 · Author: AI Agent Camp (instructor: Kohei Nakamura)Reading time: about 12 minutes

A few days after Day 1, the same five attendees return with their homework. They have one day to build one working tool for their actual job. We shadowed Day 2 — the 'I didn't think I could, but I did' moments, plus two anonymized client outcomes.

A few days after Day 1, the five attendees walked back into the same meeting room. Each carried the whiteboard memo they wrote at the end of Day 1: "three repetitive tasks I want to delegate to AI." Today's goal is one thing: turn one of those three into something that runs in your actual job, by end of day. Asked beforehand, all five said the same thing: "honestly, I don't think I can."

Day 2 in a meeting room: each attendee focused on their laptop while the instructor leans over one screen
Day 2 in a meeting room: each attendee focused on their laptop while the instructor leans over one screen

09:30Regrouping — picking the one that pays back the most

First 30 minutes: rewrite the three tasks on one sheet. The act of writing shrinks the scope — "check invoice status", "extract action items from meeting notes", "review press release in three axes". Then pick one along three axes: frequency × time × can finish alone. Day 2 is 90% the pick.

10:00Articulating the task — design with Plan Mode before writing

We bring the Day 1 mantra into real work: anything two lines or longer starts in plan mode. Each attendee feeds "goal / input / output / edge cases" to Claude Code and asks for a plan first. PR's lead got pulled back at the plan stage: "what exactly are the three axes measuring?" In their words, "every fuzzy bit in my head got exposed by the plan."

11:00Build — sticking points are permissions, formats and loops

Meeting notes' decisions auto-extracted into kanban cards (illustrative)
Meeting notes' decisions auto-extracted into kanban cards (illustrative)

Finance is building a meeting-notes → purchase tasks pipeline. The first wall is a Google Sheets permission error: "you don't get stuck on the task itself, you get stuck at the seams." Next, the extraction is unstable because each presenter talks differently. Day 1 lecture kicks in — "feed two few-shot examples" — and they recall it on their own.

Press release reviewed on three axes with comment cards (illustrative)
Press release reviewed on three axes with comment cards (illustrative)

PR wrote a press-release reviewer along three axes (reader benefit, factual accuracy, brand voice). The first run returned "5 of 5 on everything." Adding one constraint — "find three weaknesses; write 'none' only if you really must" — turned it sharp. They discovered, on their own, that lowering the bar makes the model lazy too.

12:30Lunch — "already?"

On Day 1 lunch is recovery; on Day 2 it's different. People don't stop. Finance ate a bite with the bento lid open for 20 minutes. First sign of flow. Day 1's skeptics are exactly the ones who lose track of time on Day 2.

13:30Finishing — making it actually usable

After lunch, work shifts from "running" to "fits my job as-is." Sales reshapes the output of the outbound summary into the format used in the morning huddle. Two criteria help — "can I paste this into Slack and have it read?" and "could I explain it to my manager on my own?" — and the last mile of AI output tips back toward human.

15:30Demo round — three minutes per person

An attendee smiling at their working tool while a colleague leans in (illustrative)
An attendee smiling at their working tool while a colleague leans in (illustrative)

Each person demos for three minutes. When Finance's "meeting notes → purchase list" pulled four items on the first try, the room clapped without prompting. Sales said it flat: "what used to take 45 minutes every morning takes three now," and looked more surprised than anyone.

"I didn't think I could, but I did"

What the same five people who said "honestly, I don't think I can" at 09:30 said at the end of the day.

Zero programming background — I was sure it was impossible for me. When the meeting notes finally returned a purchase list, I said something out loud without meaning to. Using it Monday.

Finance

On Day 1 it felt like 'a useful thing, but not in my world.' Today, when a press release came back with sharp comments, it became a tool of my work for the first time.

PR / Marketing

45 minutes every morning, now three. With the 40 I get back I'm starting the customer analysis I've been putting off.

Sales

Every error tempted me to say 'see, I can't.' But the instructor sat next to me and showed me how to fix each one. I think I can keep building this at home.

Admin

16:30Reflection — what Day 3 onward looks like

Last 30 minutes are the next step. Of what was built, do you (1) put it on a daily schedule, (2) share it across your team for horizontal lift, or (3) abstract it one more level to use elsewhere? Moving a "working thing" into a "thing the person next to you can use too" is Day 3's homework.

Case studies — two anonymized examples

Companies and industries are anonymized for confidentiality. The numbers are representative outcomes reconstructed from multiple real engagements, averaged at 1–3 months after the program.

Before / after workflow comparison for two case companies (illustrative)
Before / after workflow comparison for two case companies (illustrative)
CASE 01

Talent management firm T — semi-automated first-touch on booking inquiries

Managers handle a heavy stream of booking emails. They wired Claude Code + Gmail to extract requirements, score priority and draft template replies. A human still sends.

Time per inquiry
12→3 min
Daily throughput
1.7×
Build time after Day 2
2 weeks
CASE 02

Software services firm W — weekly spec-vs-code diff review

Every Friday Claude Code crawls Notion specs and the GitHub implementation, produces a diff report and posts a single Slack message as the PM's pre-review draft.

Review prep time
90→10 min/wk
Catches found
+38%
Build time after Day 2
3 weeks

Takeaways

Day 1 is the "hand one task to AI" experience. Day 2 is the day you place it inside your real job. Even non-engineers can reach a working artifact in a day. The keys are the first pick (frequency × time × solo), Plan Mode articulation, and an instructor who turns "I don't think I can" into "I did" on the spot.

For Day 1, see "Field Report: A Day Inside a Corporate AI Agent Training".

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FAQs

Who are companies T and W in the case studies?
We anonymized them and softened the industries. The numbers are representative outcomes reconstructed from multiple real corporate engagements, averaged at 1–3 months after the program.
Can I take Day 2 only?
We recommend Day 1 → Day 2 in order. Day 2 puts Day 1's concepts (plan mode, one chat one task, context) into real work, so it lands better when those are already shared.
Will I really build something working in Day 2?
All attendees reach a working template that delegates one real task to AI within Day 2. It's not production-grade yet — one file or one workflow that is practical at hand. Day 3 onward extends to operationalization.
Are subsidies available?
In Japan, MHLW's Human Resource Development Support Subsidy (reskilling track) typically refunds 75% for SMEs and 60% for large firms. Day 1 + Day 2 + review session totalling 10+ hours clears the threshold. Contact us via the form below.
Field Report Day 2: 'I Didn't Think I Could, But I Did' — Building Real Workflows in One Day