What to Look for in a Software Consulting Engagement
A checklist for both consultants and clients to ensure successful project outcomes
After years of both hiring consultants and being one, I’ve seen what separates engagements that deliver lasting value from ones that leave everyone frustrated. This checklist applies whether you’re the consultant or the client.
Before You Sign
Scope clarity is everything. The most common source of consulting disasters is a scope that both parties interpret differently. Before signing anything, write down in plain language what “done” looks like. If you can’t agree on that, you’re not ready to start.
Questions to resolve upfront:
- What are the 2-3 specific outcomes this engagement needs to produce?
- What’s explicitly out of scope?
- Who is the decision-maker on the client side?
- What does success look like at 30, 60, and 90 days?
Red flag: A client who can’t clearly articulate what they need is either unprepared or has internal alignment problems. Both are solvable, but you need to know which one before you start.
Red flag: A consultant who says yes to everything in the initial call is either naive or desperate for the work. Good consultants push back on unrealistic timelines or vague deliverables.
Communication Structure
Set expectations upfront about how you’ll communicate:
- Weekly async update: A brief written summary of what was done, what’s next, and any blockers. Non-negotiable.
- Standing sync: 30-60 minutes per week for questions and decisions. Optional depending on the engagement.
- Escalation path: Who do you contact if something urgent comes up?
Both parties should agree on response time expectations. My default: I respond to messages within 24 hours on business days. Emergency issues get same-day response.
Deliverables vs. Outcomes
There’s a dangerous trap in consulting: delivering the thing you said you’d deliver, while failing to produce the outcome the client actually wanted.
A deliverable is: “A Terraform module for provisioning EKS clusters.” An outcome is: “Data science teams can provision their own environments in under an hour.”
Good consulting always ties deliverables to outcomes. If you’re building the module but you know it won’t be adopted, say so. Clients hire consultants for judgment, not just execution.
Knowledge Transfer
One of the most common complaints I hear from clients about past consultants: “They built it, then they left, and now nobody knows how it works.”
Every engagement should include:
- Documentation written for the people who will maintain the work
- At least one working session where you walk through what was built
- Code that the team can modify, not just run
I measure knowledge transfer by asking: Could the client debug a production issue at 3am without me? If not, the engagement isn’t done.
Signs an Engagement Is Going Well
- Client team members are asking good questions and pushing back on decisions
- Scope is stable or changes are explicitly discussed and agreed upon
- Blockers are surfaced early, not discovered at the deadline
- The consultant is learning domain context from the client, not just applying generic patterns
Signs an Engagement Is Going Sideways
- The client is disengaged — missing syncs, slow to review, no feedback
- Requirements keep changing without acknowledgment that scope is shifting
- The consultant is working in isolation and delivering “surprises”
- Either party is avoiding a difficult conversation
When an engagement starts going sideways, the sooner it’s addressed, the better. Most issues are recoverable early. Few are recoverable when they surface at the end.
Ending Well
A good consulting engagement ends with:
- All deliverables handed off and documented
- A clear transition plan or “parking lot” for future work
- An honest retrospective: what went well, what didn’t
Don’t skip the retrospective. Even a 30-minute conversation about lessons learned makes the next engagement better — for both parties.
About the Author
Joseph Haaga is a Principal Software Engineer & MLOps Consultant based in Washington, D.C. He specializes in ML infrastructure, data platforms, and cloud architecture.
Available for Consulting