Focusing Where Mountain Goat Software Can Have the Most Impact

The Seven Organizational Shifts That Determine Whether Your AI Investment Pays Off

Drawing on Mik Kersten's forthcoming book 'Output to Outcome', this piece outlines seven interdependent organizational shifts enterprises must make to realize ROI from AI investments. The shifts cover restructuring around value streams instead of functions, connecting work to strategic outcomes, unifying planning cadences, applying software modularity principles to org design, aligning objectives to shared ownership, segmenting value streams by domain (core, platform, incubation, transformation), and evolving leadership from oversight roles to hands-on 'outcome managers'. The core argument is that AI amplifies existing organizational dysfunction — adding AI to an unrestructured system produces more output without better outcomes — and that all seven shifts must be made as a system, not selectively.

A Seasoned Tester's Crystal Ball: Appropriate speed for the conditions, deliberately

A veteran tester reflects on lessons learned during an agile transformation at F-Secure in the early 2000s, drawing parallels to today's AI-driven overwhelm. The key insight: when CI/CD eliminated natural waiting periods that had fostered team learning and cross-pollination, the team had to deliberately carve out time for improvement. The same principle applies now — developers and testers have agency to choose an appropriate pace when adopting AI, rather than feeling compelled to match the fastest adopters.

We Tried Agile and It Didn’t Work

When teams say 'we tried agile and it didn't work,' leaders should treat it as diagnostic data rather than resistance. Common failure modes include adopting agile ceremonies without changing decision-making, weak product ownership, excessive work in progress, symbolic empowerment, and leaders delegating agile to teams without changing the surrounding system. The post outlines a five-pillar diagnostic framework (mindset, practices, roles, teamwork, outside-the-team support) and a practical recovery path: acknowledge the previous experience honestly, name a concrete outcome, pick one small visible improvement, maintain an improvement backlog, and inspect results. Skeptics should be engaged as sources of information rather than dismissed. If the word 'agile' carries too much baggage, leaders can pursue agile goals under different framing.

Why Scrum Isn’t Working Even Though You’re Doing Scrum

Organizations often implement all the Scrum ceremonies and roles yet still fail to see the expected benefits. The core problems are: Scrum events becoming empty rituals rather than value-generating activities, sprint interruptions being treated as costless when they erode team trust and focus, organizational lack of prioritization pushing too many demands onto teams, leaders not creating the right environment for self-managing teams, Scrum Masters staying too close to the team instead of removing organizational impediments, and excessive rules making Scrum feel like bureaucracy. The recommended approach is to apply Scrum's own inspect-and-adapt principle to improve Scrum itself — identifying the biggest root cause and experimenting with one change at a time rather than attempting a big-bang reset.

A Seasoned Tester's Crystal Ball: Faking plans is easier than fighting plans

Kinh nghiệm từ một tester dày dặn cho thấy việc lập kế hoạch kiểm thử chi tiết bị bỏ qua trong dự án giá cố định, dù phát hiện lỗi €25.000 sớm. AI hỗ trợ giao tiếp nhưng thay thế sự hợp tác thật sự, khi lập kế hoạch chỉ là hình thức. Bài học: AI khiến mọi người lười xây dựng mô hình tư duy riêng, hợp tác trực tiếp quan trọng hơn giao nộp tài liệu, và đôi khi nên chấp nhận kế hoạch hình thức để hoàn thành công việc thực tế.

Lập trình viên nên đọc bài này để hiểu cách quản lý dự án thực tế khi các quy trình kiểm thử bị bỏ qua, và cách cân nhắc giữa sự hợp tác trực tiếp với đội và việc tuân thủ các tài liệu giả tạo để tránh bị bỏ ngỏ trong môi trường công việc cạnh tranh.