Partner Basecamp · Cohort 8

Programme Satisfaction

Positive NPS of +43 — promoters outweigh detractors with moderate passive presence.

+43NPS · n=37

54% Promoters35% Passives11% Detractors

95% CI: +21 → +65 · True NPS lies within this range with 95% confidence (n=37 respondents)

Confidence Arc

Strong end-of-Day-1 build confidence — cohort leaves Day 1 ready to apply Claude in client work (mean 4.0/5).

4.0end-of-D1 build / 5

4.1D2 Design / 5

4.2D2 Commercial / 5

4.3D2 Build / 5

Audience

48 participants across 8 organisations — Transformation Lead majority with applying in practice the most common AI experience level.

Top Organisations

Deloitte (21) PwC (8) Ascendion (4) Fractal Analytics (4) Sia (4)

Voice of Participant

What participants said — dominant theme from each NPS segment.

Promoters

Participants valued hands-on tool exploration with peers, relevant content depth, and engaging delivery matched to consultant capabilities.

Passives

Inconsistent experience across days and concerns about technical depth relative to participants' prior Claude exposure and developer experience.

Detractors

Non-technical attendees struggled with pace and wanted more guided live demos and structured group practice before independent exercises.

Function	Practitioner	Sr Practitioner	Mgr / Sr Mgr	Director+	Partner / MD	Total
Engineering	2	5	2	2	1	12
Architecture	3	3	2	2	–	10
Business Leadership	1	–	3	–	5	9
Project / Engmt	11	2	3	1	–	17

Function

Practitioner

Sr Practitioner

Mgr / Sr Mgr

Director+

Partner / MD

Total

Engineering

Architecture

–

Business Leadership

–

Project / Engmt

–

Segment	Exploring	Applying	Delivering	Frontier	n
Transformation Lead	31%	42%	12%	15%	26
Developer	17%	42%	33%	8%	12
Architect	—	20%	40%	40%	10

Segment

Exploring

Applying

Delivering

Frontier

Transformation Lead

31%

42%

12%

15%

Developer

17%

42%

33%

Architect

—

20%

40%

Segment	Exploring	Applying	Delivering	Frontier	n
Practitioner (0-4 years in role)	29%	53%	12%	6%	17
Manager or Senior Manager	30%	40%	10%	20%	10
Senior practitioner (5–9 years)	20%	30%	50%	—	10
Partner, Managing Director, or Executive	—	33%	17%	50%	6
Director, Senior Director, or Principal	—	—	40%	60%	5

Segment

Exploring

Applying

Delivering

Frontier

Practitioner (0-4 years in role)

29%

53%

12%

Manager or Senior Manager

30%

40%

10%

20%

Senior practitioner (5–9 years)

20%

30%

50%

—

Partner, Managing Director, or Executive

—

33%

17%

50%

Director, Senior Director, or Principal

—

40%

60%

Segment	Too basic	About right	Too advanced	n
Transformation Lead	8%	73%	19%	26
Developer	—	100%	—	12
Architect	20%	70%	10%	10

Segment

Too basic

About right

Too advanced

Transformation Lead

73%

19%

Developer

—

100%

—

Architect

20%

70%

10%

Segment	Too basic	About right	Too advanced	n
Applying in practice	—	78%	22%	18
Delivering independently	9%	82%	9%	11
Learning and exploring	—	90%	10%	10
Operating at the frontier	33%	67%	—	9

Segment

Too basic

About right

Too advanced

Applying in practice

—

78%

22%

Delivering independently

82%

Learning and exploring

—

90%

10%

Operating at the frontier

33%

67%

—

Segment	Too slow	Well paced	Too fast	n
Transformation Lead	8%	81%	12%	26
Developer	—	92%	8%	12
Architect	10%	90%	—	10

Segment

Too slow

Well paced

Too fast

Transformation Lead

81%

12%

Developer

—

92%

Architect

10%

90%

—

Segment	Too slow	Well paced	Too fast	n
Applying in practice	11%	78%	11%	18
Delivering independently	—	100%	—	11
Learning and exploring	—	80%	20%	10
Operating at the frontier	11%	89%	—	9

Segment

Too slow

Well paced

Too fast

Applying in practice

11%

78%

11%

Delivering independently

—

100%

—

Learning and exploring

—

80%

20%

Operating at the frontier

11%

89%

—

Cohort	0	1	2	3	4	5	6	7	8	9	10
Cohort 8							4	7	6	4	16

Cohort

Cohort 8

1	2	3	4	5	Mean
—	3%	11%	57%	30%	4.14

Mean

—

11%

57%

30%

4.14

1	2	3	4	5	Mean
—	—	16%	49%	35%	4.19

Mean

—

16%

49%

35%

4.19

1	2	3	4	5	Mean
—	—	14%	41%	46%	4.32

Mean

—

14%

41%

46%

4.32

NPS Reason

n=26 responses · grouped by NPS segment

Promotersscore 9–10 · 14 responses

1Well matched against the product capabilities and how to think about the larger set of questions for clients.10

2Interactive, engaging10

3Loved the dedicated time to learn about, and get hands onto the tools. Great to sit with colleagues, competitors, and learn about anthropic tools and application10

4Extremely insightful, great content and activities.10

5Amazing Anthropic Team and phenomenal content and execution! This team deserves a round of applause and thanks 🙏🏽 for their excellent delivery!10

6This is the right level of content for anyone at any level.10

7Facilitatators10

8Extremely cool event, really good to be in the room to see where everyone's at and get to focus on claude building skills for two whole days10

9I thought this was really cool, from a networking perspective to also feeling like Anthropic truly values our partnership. I was able to learn a ton about the entire Anthropic suite of software, models, etc Anthropic has.10

10The mix of hands-on exercises coupled with the practical slides / sessions felt like a good mix of learn/do. The inventory management exercise at the beginning of day 1 felt like it ran a bit too long, but for those who are newer it was a good shakedown.10

11Was an amazing challenge. I learned a lot & was able to skill up quickly from having little Claude code experience.10

12I really enjoyed the content!9

13Depth of training materials9

14this training was excellent. my only suggestion is diving even deeper into building eval frameworks as this is going to be a critical piece of how we build credibility with our clients. i’d like to get some additional reps in with building & shipping realistic solutions, especially in a collaborative framework9

Passivesscore 7–8 · 8 responses

1Very intensive with a lot to learn8

2Some reservations about whether they will be able to get full use out of the sessions given level of exposure to Claude Code and level of explanation/ facilitation ahead of each exercise. Would depend on their preparation or exposure before attending8

3Great course, but very few of my peers are experienced developers and a lot of this material is too technical.8

4Intro to a lotta cool new stuff.7

5I liked it :)7

6Evaluation and process7

7Day 1 was not the same experience as Day 2 in terms of admin setup7

8I do wish this course was more formated in a ‘I do, we do, you do’ format. I wish more examples or demos were done7

Detractorsscore 0–6 · 4 responses

1I think I was a little behind in almost all of the sessions, would be helpful to get a live demo in all the sessions to understand how to get working because I felt a little lost sometimes6

2Felt like course wasn't beginner friendly. Was a lot to take in coming from a non technical background.6

3Good intro to Claude code but I wish there was some more building rather than just running notebooks, etc although they were good to help learn the process6

4Was a cool experience, but felt like this could have been done online in the current format. I would have appreciated more guided live instruction. They seemed very concerned about not “lecturing” for too long, but I would have liked more. It would have been nice if we did the first couple exercises as a group before doing individual work.6

Most Valuable

What one takeaway will you share with a colleague or client? · n=18 responses

1Anthropic positioning for their product is more aligned to software architecture than they think.

2Usuage of playwright mcp server

3We should all be using Claude or a similar AI.

4Everything i have learned

5This training raises the bar for all AI-based trainings!

6That it was awesome and how to build an eval

7That is a world full of opportunities ahead

8Process of using app

9Prompt caching

10Eval methods

11Knowledge

12How important it is to stay up on new features and releases, which is almost a full-time job with the Claude ecosystem!

13eval frameworks are critical in defining the accuracy of AI solutions

14That Anthropic has just about everything you need to go from 0-100 when it comes to integrating AI the right way.

15Lots of times we hear that clients don't know how they can trust AI solutions or clearly evaluate how they're doing. I now have a framework (evals) to robustly test AI solutions that I can bring confidently to clients and colleagues. That was super helpful.

16Importance of evals

17potential is unlimited!

18Come for the food… While I struggled with the labs(and my ‘outer), it did show the importance of these components in our agent building. I do like the fact Anthropic stresses that developers need to test the models decide which is best for consistent behavior and response, rather than what’s new and shiny. Overall a good session that even non-technical users would benefit from.

30-Day Intentions

What will you build for yourself or apply at work? · n=27 responses

1I will be enhancing my ways context progressive disclosure system with more evaluation agents.i also plan on enhancing our intelligence gateway product to build a corpus of performance evaluations too.

2Agentic ai application and deploy in cloud

3A bunch if dashboards

4Application for prod monitoring loads

5Call summ automation

6Continue working with Claude code capabilities

7Apply Claude with PowerPoint creation and emails.

8Plan to build custom agents to automate many time sucking tasks into repeatable routines

9Agents to automate processes and workflows. Features and bug fixes for internal tools

10More than I can capture in words 😎💪🏾!

11I will advance my personal workflows and agents.

12Im going to build a process for us to evaluate all of our ai projects.

13Some playwright tool managed by Claude to accelerate my admin work

14Health care payer apps

15A personal agent to manage day to day repeatable tasks

16Agent team

17Update some of the hacked ways I’ve built older agents using some of these practices

18Use AI for customer problems

19Probably will further productionize the RFP response but I build our hackathon

20training materials for my team to learn how to build production-ready AI systems

21Some custom agents for numerous tasks. I am also a part time student so I’d love to figure out how I can integrate Claude into my school.

22More Claude code usage for technical aspects of the cloud modernization effort.

23Cowork workflows. I just got access to it in my enterprise environment, super excited to try it. I also will be developing with the agent SDK, but don't know specifically what I want to build yet.

24I might expand on the RFP agent to be usable for real clients.

25Build agents

26Automating manual excel analyses for clients & log analyses

27Actively working with other teams on building agents. And while we do work in Claude for much of our work we ultimately have to support our customers with their approved models

Day 1 responses	48
Day 2 responses	37 (77% of Day 1)
Matched pairs	34 (92% of Day 2)
Orgs resolved	48 of 48 respondents matched to named org
Day 2-only respondents	3 (8.1%) — suppresses NPS by 1 points; no Day 1 data, excluded from persona & confidence analysis

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