Can you provide an example of when you utilized your influence to achieve a specific outcome?

Question

Anonymous · Accepted Answer

SITUATION

In large-scale platform and ML infrastructure work, direct authority is often
limited—you’re building shared systems that dozens of product teams depend on,
but many of those engineers don’t report to you. At Mailchimp, for example, my
ML platform org was tasked with rolling out a unified SDK to accelerate model
development and deployment. The SDK promised faster iteration (cutting
time-to-deploy from weeks → days) and consistency across training, inference,
and monitoring. However, adoption required product engineering teams to change
their workflows, rewrite portions of their pipelines, and take on risk as early
guinea pigs. I had no direct authority to mandate adoption—success depended
entirely on my ability to influence.

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TASK

My task was to drive cross-org alignment and adoption of the SDK across three
product teams within two quarters. Specifically, I needed to:

1. Build trust so teams saw this as an accelerator, not an imposed tax.

2. Show tangible value early so adoption felt worth the investment.

3. Influence senior stakeholders (directors of product and engineering) to
    sponsor adoption, despite competing priorities and risk aversion.

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ACTION

I approached this using influence through context, credibility, and co-creation:

1. Framing in business terms: Instead of selling the SDK as “infra
    modernization,” I positioned it as “reducing time-to-market for ML-powered
    features by 70%.” I shared models showing how adoption could lift campaign
    personalization CTR by 10–12% if retrain cycles shrank. This connected infra
    work directly to revenue and customer outcomes.

2. Building credibility through depth: I immersed myself in the product teams’
    PRDs and workflows, understanding their pain points firsthand. For example,
    one team struggled with retraining models fast enough to capture seasonal
    shopping trends. I tailored the SDK pitch to solve that exact pain, making
    the value undeniable.

3. Creating early wins with champions: I identified one Staff engineer on a
    partner team who was respected widely. I co-developed a pilot with him,
    ensuring his team saw results first: their retrain lag dropped from 12 days
    → 4.5 days, boosting recommendation freshness. I highlighted his team’s
    leadership publicly, creating FOMO for others.

4. Influencing up and across: I presented the pilot results in product
    leadership reviews, focusing on business impact (“fresher recommendations,
    higher engagement”) while letting the champion engineer demo the technical
    details. This gave leaders confidence and peers a relatable success story.

5. Lowering adoption friction: I allocated one of my engineers to co-pilot
    migrations with each partner team, ensuring no one felt abandoned. This
    support was framed not as “oversight” but as “collaboration.”

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RESULT

Within two quarters:

* Three product teams adopted the SDK, covering ~60% of ML-powered features.

* Retrain cycle time dropped from 10–14 days → ~5 days across adopters.

* Inference consistency improved, cutting error rates by 18% and reducing
   incident MTTR from 75m → 40m.

* Product leaders cited the SDK rollout as a “velocity unlock” in quarterly
   reviews.

* Most importantly, adoption momentum became self-sustaining—engineers from
   other teams proactively asked to onboard, and the SDK became the de facto
   standard across the org.

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TAKEAWAY

This experience reinforced that influence is about context, credibility, and
co-creation. By framing infra changes in terms of business outcomes, deeply
understanding partner workflows, and creating early wins with champions, I was
able to drive adoption and impact without authority. Influence, done right,
turns shared ownership into a multiplier of impact.

Anonymous · Answer

While working at ABC, I noticed that internal customers were creating expensive
resources but still paying per-use rates. This meant they had large resources
allocated but were not fully utilizing them, leading to inefficiencies in both
our fleet and overall system performance. It became clear that there were
misaligned incentives.
Task:
I needed to influence multiple internal teams and stakeholders to resize their
resources to better align utilization with actual demand. This required
gathering data, negotiating with internal customers, and proposing a solution
that both addressed the technical inefficiencies and fit within their
operational requirements.
Action:
 1. Data Gathering: I asked my engineers to gather data on resource utilization
    across internal customers. We discovered that most customers were using less
    than 5% of their provisioned capacity.
 2. Engagement with Stakeholders: I began by reaching out to two of the largest
    internal users—XYZ and PQR—both of which I had close relationships with. I
    framed the problem as a multi-phased solution that would allow them to
    resize their resources gradually without impacting their services.
 3. Cross-team Alignment: I then engaged with the Front-End (FE) team and its
    Senior Manager to inform them of this opportunity to shape the traffic and
    reduce strain on the backend fleet. This led to further discussions about
    aligning future traffic patterns to optimize fleet usage.
 4. Initiating Pricing Discussions: With the success of the initial efforts, I
    initiated discussions around refining the internal pricing model, presenting
    data to show that many more customers could benefit from resizing, thereby
    reducing backend load and unnecessary resource allocation.

Result:
 * Backend Fleet Reduction: We successfully reduced the backend fleet size by
   7-9%, leading to a reduction in overall system load and minimizing metadata
   overhead.
 * Cost Savings: Customers were able to save costs as well by reducing their
   reliance on over-provisioned resources and lowering the number of workers
   required for their applications.
 * System Improvements: By pushing out scaling cliffs for the load aggregator
   service, we avoided potential bottlenecks, improving operational stability.
 * Pricing Strategy Refinement: This work led to ongoing refinements in ABC's
   internal pricing model, aiming to align more closely with public pricing or
   move towards a more robust per-use product.

Reflection:
One thing I would do differently is celebrate the success more broadly across
teams. I later realized that while the FE team was actively working on resizing
streams, the Orchestration team had been giving conflicting advice to customers,
suggesting they over-provision when in doubt. Greater coordination and
communication could have avoided this issue and created a more unified effort.

Anonymous · Answer

In Q1 2023, as the SDM for Datapath Responder Runtime team, I was told by my
leadership to drop all the project work and focus on Efficiency work to reduce
the cost of service as it was a directive from the VP. This was conflicting with
my team’s goal to get certified to handle critical data as a platform. One of
the projects for critical data certification was to support HTTPS instead of
HTTP. The approach we took was to move the web container from the current custom
solution to Amazon standard Coral Web server. There were 3 engineers working on
this project and we had completed about 60% of the work. Stopping this work to
pick up another project which had high chances of failure would mean
demoralizing the team and delaying the certification timelines. SDE’s promotion
to Sr was tied to this project as well.
I had to use my influence with my leadership to keep funding this project. I
presented my case that moving to Coral Web server would make the platform more
efficient due to variety of performance knobs such as better thread scheduling,
more efficient metric emission, etc. I also leveraged the TPM and Security
Certifiers to provide a strong business case to not delay the certification
process. Finally, I also committed to finishing the web server migration and the
efficiency experiments with performance knobs by mid Q2 to realize efficiency
gains from this work before the Q3 and Q4 peaks.

Anonymous · Answer

At Auctane, while working on a APIs for a reporting service, my developer was
blocked due to product managers input. The product manager wanted to add more
search parameters to the API, I understand that any delays would impact the
project timeline. I had built a good rappot with this product manager and used
my influcene to prioritize my devs request. This unblocked my developer to move
forward. It is important to understand the dynamics in an org to make an
influence without authority.

Anonymous · Answer

At Auctane, while working on a APIs for a reporting service, my developer was
blocked due to product managers input. The product manager wanted to add more
search parameters to the API, I understand that any delays would impact the
project timeline. I had built a good rappot with this product manager and used
my influcene to prioritize my devs request. This unblocked my developer to move
forward. It is important to understand the dynamics in an org to make an
influence without authority.

Anonymous · Answer

At Auctane, while working on a APIs for a reporting service, my developer was
blocked due to product managers input. I understand that any delays would impact
the project timeline. I had built a good rappot with this product manager and
used my influcene to prioritize my devs request. This unblocked my developer to
move forward.

Anonymous · Answer

At Auctane, while working on a APIs for a reporting service, my developer was
blocked due to product managers input. I understand that any delays would impact
the project timeline. I had built a good rappot with this product manager and
used my influcene to prioritize my devs request. This unblocked my developer to
move forward.

Can you provide an example of when you utilized your influence to achieve a specific outcome?

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